diff --git a/COURSE_CATALOG.generated.json b/COURSE_CATALOG.generated.json index 4689158007..1f391c8368 100644 --- a/COURSE_CATALOG.generated.json +++ b/COURSE_CATALOG.generated.json @@ -1169,6 +1169,36 @@ "requires_wsl": false, "executable_locally": true }, + { + "path": "GameTheory/GameTheory-06e-Open-Source-Game-Theory.ipynb", + "title": "GameTheory-06e : Transparence des programmes et issue du Dilemme du prisonnier one-shot", + "serie": "GameTheory", + "sous_serie": "", + "kernel": "Python 3 (ipykernel)", + "status": "READY", + "maturity": "ALPHA", + "editorial": "ALPHA", + "reproducibility": "EXECUTED", + "scientific_review": "UNREVIEWED", + "last_success_sha": "6b327a9bf", + "executed_at": "2026-09-09T05:59:10+02:00", + "forensic_category": "A_ALL_EXEC_OK", + "duree_estimee": "15min", + "owner_logique": "po-2024", + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 31, + "cells_code": 7, + "cells_markdown": 24, + "cells_with_outputs": 5, + "cells_without_outputs": 0, + "requires_api": false, + "requires_gpu": false, + "requires_cloud": false, + "requires_wsl": false, + "executable_locally": true + }, { "path": "GameTheory/GameTheory-07-ExtensiveForm-Csharp.ipynb", "title": "GameTheory-07-ExtensiveForm (Twin C#)", @@ -2309,6 +2339,36 @@ "requires_wsl": false, "executable_locally": true }, + { + "path": "GameTheory/GameTheory-16e-LLM-Players-Othman-Sandholm.ipynb", + "title": "GameTheory-16e : Pilote — joueurs LLM hétérogènes sur le mécanisme Othman–Sandholm (Proposition 6)", + "serie": "GameTheory", + "sous_serie": "", + "kernel": "Python 3", + "status": "READY", + "maturity": "BETA", + "editorial": "BETA", + "reproducibility": "EXECUTED", + "scientific_review": "UNREVIEWED", + "last_success_sha": "453413dcb", + "executed_at": "2026-09-10T02:36:29+02:00", + "forensic_category": "A_ALL_EXEC_OK", + "duree_estimee": "45min", + "owner_logique": "po-2024", + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 30, + "cells_code": 15, + "cells_markdown": 15, + "cells_with_outputs": 12, + "cells_without_outputs": 0, + "requires_api": true, + "requires_gpu": false, + "requires_cloud": false, + "requires_wsl": false, + "executable_locally": false + }, { "path": "GameTheory/GameTheory-17-MultiAgent-RL-Csharp.ipynb", "title": "GameTheory-17 (C#) : Multi-Agent Reinforcement Learning — Self-Play, FP, NFSP, PSRO", @@ -3001,7 +3061,7 @@ }, { "path": "GameTheory/SocialChoice/04-Computational-Aggregation-SAT-Z3.ipynb", - "title": "SocialChoice 04 - Agregation Computationnelle : SAT et Z3", + "title": "SocialChoice 04 - Agrégation Computationnelle : SAT et Z3", "serie": "GameTheory", "sous_serie": "SocialChoice", "kernel": "Python 3 (WSL)", @@ -4128,10 +4188,10 @@ "last_validation": "2026-08-31", "last_validator": "jessynoo@gmail.com", "issue_pr_associee": "#13589, #13606", - "cells_total": 29, - "cells_code": 12, + "cells_total": 30, + "cells_code": 13, "cells_markdown": 17, - "cells_with_outputs": 8, + "cells_with_outputs": 9, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -4188,9 +4248,9 @@ "last_validation": "2026-09-05", "last_validator": "jsboige@gmail.com", "issue_pr_associee": "#14209, #14715", - "cells_total": 26, + "cells_total": 27, "cells_code": 12, - "cells_markdown": 14, + "cells_markdown": 15, "cells_with_outputs": 7, "cells_without_outputs": 1, "requires_api": true, @@ -4218,9 +4278,9 @@ "last_validation": "2026-08-23", "last_validator": "jsboige@gmail.com", "issue_pr_associee": "#11947, #12591", - "cells_total": 30, + "cells_total": 31, "cells_code": 11, - "cells_markdown": 19, + "cells_markdown": 20, "cells_with_outputs": 1, "cells_without_outputs": 1, "requires_api": true, @@ -4248,9 +4308,9 @@ "last_validation": "2026-08-24", "last_validator": "jsboige@gmail.com", "issue_pr_associee": "#12485, #12511", - "cells_total": 59, + "cells_total": 60, "cells_code": 19, - "cells_markdown": 40, + "cells_markdown": 41, "cells_with_outputs": 13, "cells_without_outputs": 1, "requires_api": true, @@ -4278,9 +4338,9 @@ "last_validation": "2026-08-30", "last_validator": "jsboige@gmail.com", "issue_pr_associee": "#10038, #13542", - "cells_total": 59, + "cells_total": 60, "cells_code": 19, - "cells_markdown": 40, + "cells_markdown": 41, "cells_with_outputs": 13, "cells_without_outputs": 1, "requires_api": true, @@ -4308,9 +4368,9 @@ "last_validation": "2026-08-26", "last_validator": "jsboige@gmail.com", "issue_pr_associee": "#12484, #12514", - "cells_total": 27, + "cells_total": 28, "cells_code": 12, - "cells_markdown": 15, + "cells_markdown": 16, "cells_with_outputs": 7, "cells_without_outputs": 1, "requires_api": true, @@ -6708,9 +6768,9 @@ "last_validation": "2026-09-03", "last_validator": "jsboige@gmail.com", "issue_pr_associee": "#13891, #14272", - "cells_total": 34, + "cells_total": 35, "cells_code": 15, - "cells_markdown": 19, + "cells_markdown": 20, "cells_with_outputs": 12, "cells_without_outputs": 0, "requires_api": false, @@ -6891,7 +6951,7 @@ "cells_total": 30, "cells_code": 13, "cells_markdown": 17, - "cells_with_outputs": 12, + "cells_with_outputs": 9, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -8388,10 +8448,10 @@ "last_validation": "2026-07-30", "last_validator": "jessynoo@gmail.com", "issue_pr_associee": "#8843", - "cells_total": 39, - "cells_code": 12, - "cells_markdown": 27, - "cells_with_outputs": 8, + "cells_total": 41, + "cells_code": 13, + "cells_markdown": 28, + "cells_with_outputs": 9, "cells_without_outputs": 0, "requires_api": true, "requires_gpu": false, @@ -8448,10 +8508,10 @@ "last_validation": "2026-08-16", "last_validator": "jsboige@gmail.com", "issue_pr_associee": "#11168, #11181", - "cells_total": 63, - "cells_code": 19, - "cells_markdown": 44, - "cells_with_outputs": 14, + "cells_total": 66, + "cells_code": 21, + "cells_markdown": 45, + "cells_with_outputs": 16, "cells_without_outputs": 0, "requires_api": true, "requires_gpu": false, @@ -9468,10 +9528,10 @@ "last_validation": "2026-08-31", "last_validator": "jessynoo@gmail.com", "issue_pr_associee": "#13757, #13783", - "cells_total": 16, - "cells_code": 8, - "cells_markdown": 8, - "cells_with_outputs": 4, + "cells_total": 18, + "cells_code": 9, + "cells_markdown": 9, + "cells_with_outputs": 5, "cells_without_outputs": 0, "requires_api": true, "requires_gpu": false, @@ -10693,15 +10753,15 @@ "last_success_sha": "d98c041d9", "executed_at": "2026-09-04T05:26:01+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "45min", + "duree_estimee": "1h", "owner_logique": "po-2025", "last_validation": "2026-09-04", "last_validator": "jsboige@gmail.com", "issue_pr_associee": "#13596, #14557", - "cells_total": 50, - "cells_code": 19, - "cells_markdown": 31, - "cells_with_outputs": 19, + "cells_total": 53, + "cells_code": 20, + "cells_markdown": 33, + "cells_with_outputs": 20, "cells_without_outputs": 0, "requires_api": true, "requires_gpu": true, @@ -14748,10 +14808,10 @@ "last_validation": "2026-08-31", "last_validator": "jsboige@gmail.com", "issue_pr_associee": "#11947, #12065", - "cells_total": 57, - "cells_code": 25, - "cells_markdown": 32, - "cells_with_outputs": 21, + "cells_total": 59, + "cells_code": 26, + "cells_markdown": 33, + "cells_with_outputs": 22, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -14803,15 +14863,15 @@ "last_success_sha": "9b60d6b89", "executed_at": "2026-09-06T15:21:41+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "45min", + "duree_estimee": "1h", "owner_logique": "po-2023", "last_validation": "2026-09-06", "last_validator": "jsboige@gmail.com", "issue_pr_associee": "#14842, #14852", - "cells_total": 80, - "cells_code": 29, - "cells_markdown": 51, - "cells_with_outputs": 24, + "cells_total": 83, + "cells_code": 30, + "cells_markdown": 53, + "cells_with_outputs": 25, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -17233,15 +17293,15 @@ "last_success_sha": "3443f1f6f", "executed_at": "2026-09-05T12:10:53+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "45min", + "duree_estimee": "1h", "owner_logique": "po-2026", "last_validation": "2026-09-05", "last_validator": "jsboige@gmail.com", "issue_pr_associee": "#14209, #14713", - "cells_total": 50, - "cells_code": 19, - "cells_markdown": 31, - "cells_with_outputs": 16, + "cells_total": 62, + "cells_code": 22, + "cells_markdown": 40, + "cells_with_outputs": 19, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": true, @@ -17328,9 +17388,9 @@ "last_validation": "2026-08-29", "last_validator": "jsboige@gmail.com", "issue_pr_associee": "#9434, #13133", - "cells_total": 45, + "cells_total": 49, "cells_code": 16, - "cells_markdown": 29, + "cells_markdown": 33, "cells_with_outputs": 12, "cells_without_outputs": 0, "requires_api": false, @@ -17988,9 +18048,9 @@ "last_validation": "2026-09-05", "last_validator": "jsboige@gmail.com", "issue_pr_associee": "#14209, #14713", - "cells_total": 22, + "cells_total": 26, "cells_code": 10, - "cells_markdown": 12, + "cells_markdown": 16, "cells_with_outputs": 10, "cells_without_outputs": 0, "requires_api": false, @@ -19739,6 +19799,36 @@ "requires_wsl": false, "executable_locally": true }, + { + "path": "RL/rl_1c_prolog_distillation.ipynb", + "title": "Distiller une politique RL en programme Prolog exécutable : T, T-bar et S", + "serie": "RL", + "sous_serie": "", + "kernel": "Python 3", + "status": "READY", + "maturity": "BETA", + "editorial": "BETA", + "reproducibility": "EXECUTED", + "scientific_review": "UNREVIEWED", + "last_success_sha": "3555ce783", + "executed_at": "2026-09-09T05:09:24+02:00", + "forensic_category": "A_ALL_EXEC_OK", + "duree_estimee": "45min", + "owner_logique": "po-2025", + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 58, + "cells_code": 22, + "cells_markdown": 36, + "cells_with_outputs": 18, + "cells_without_outputs": 0, + "requires_api": false, + "requires_gpu": false, + "requires_cloud": false, + "requires_wsl": false, + "executable_locally": true + }, { "path": "RL/rl_2_wrappers_sauvegarde_callbacks.ipynb", "title": "Notebook 2 – Wrappers Gym, Sauvegarde/Chargement, Multiprocessing, Callbacks et Environnements Personnalisés", @@ -21700,7 +21790,7 @@ "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "777a7a378f", + "last_success_sha": "777a7a378", "executed_at": "2026-09-07T11:04:44+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", @@ -23640,7 +23730,7 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-1-Introduction.ipynb", + "path": "Search/Part4-Metaheuristics/MGS-01-Introduction.ipynb", "title": "MGS-1 : Introduction a MetaGeneticSharp et au moteur autonome", "serie": "Search", "sous_serie": "Part4-Metaheuristics", @@ -23650,14 +23740,14 @@ "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "a609ec087", - "executed_at": "2026-08-20T18:25:09+02:00", + "last_success_sha": "7331d304d", + "executed_at": "2026-09-09T21:59:45+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "owner_logique": "po-2025", - "last_validation": "2026-08-20", - "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#1203, #11941", + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", "cells_total": 25, "cells_code": 9, "cells_markdown": 16, @@ -23670,8 +23760,8 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-10-CenterBias.ipynb", - "title": "MGS-10 : Le test du biais central — un optimiseur « sans biais en zéro » passe-t-il l'épreuve du déplacement ?", + "path": "Search/Part4-Metaheuristics/MGS-02-Composition.ipynb", + "title": "MGS-2 : Composition de métaheuristiques -- Match et primitives de contrôle", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", @@ -23680,18 +23770,18 @@ "editorial": "ALPHA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "59f7f79fa", - "executed_at": "2026-08-31T19:49:56+02:00", + "last_success_sha": "7331d304d", + "executed_at": "2026-09-09T21:59:45+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "30min", + "duree_estimee": "45min", "owner_logique": "po-2025", - "last_validation": "2026-08-31", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#13589, #13606", - "cells_total": 19, - "cells_code": 8, - "cells_markdown": 11, - "cells_with_outputs": 8, + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 29, + "cells_code": 11, + "cells_markdown": 18, + "cells_with_outputs": 11, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -23700,8 +23790,8 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-11-IslandSynergy.ipynb", - "title": "MGS-11 : Synergie d'iles complementaires -- exploration et exploitation ensemble", + "path": "Search/Part4-Metaheuristics/MGS-03-Eukaryote.ipynb", + "title": "MGS-3 : L'Eukaryote -- sous-populations et chromosomes composites", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", @@ -23710,18 +23800,18 @@ "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "59f7f79fa", - "executed_at": "2026-08-31T19:49:56+02:00", + "last_success_sha": "7331d304d", + "executed_at": "2026-09-09T21:59:45+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "30min", + "duree_estimee": "45min", "owner_logique": "po-2025", - "last_validation": "2026-08-31", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#13589, #13606", - "cells_total": 16, - "cells_code": 7, - "cells_markdown": 9, - "cells_with_outputs": 7, + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 28, + "cells_code": 10, + "cells_markdown": 18, + "cells_with_outputs": 10, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -23730,28 +23820,28 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-12-AxisAlignment.ipynb", - "title": "MGS-12 : Le test de l'alignement d'axes -- un optimiseur résiste-t-il à la rotation du paysage ?", + "path": "Search/Part4-Metaheuristics/MGS-04-Islands.ipynb", + "title": "MGS-4 : Le Modèle Insulaire -- populations structurees et migration", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", "status": "READY", - "maturity": "ALPHA", - "editorial": "ALPHA", + "maturity": "BETA", + "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "59f7f79fa", - "executed_at": "2026-08-31T19:49:56+02:00", + "last_success_sha": "7331d304d", + "executed_at": "2026-09-09T21:59:45+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "owner_logique": "po-2025", - "last_validation": "2026-08-31", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#13589, #13606", - "cells_total": 27, - "cells_code": 10, - "cells_markdown": 17, - "cells_with_outputs": 10, + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 36, + "cells_code": 13, + "cells_markdown": 23, + "cells_with_outputs": 13, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -23760,29 +23850,29 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-13-LandscapeDebias.ipynb", - "title": "MGS-13 — Visualiser les paysages dé-biaisés : pourquoi la rotation casse la séparabilité", + "path": "Search/Part4-Metaheuristics/MGS-05-CompoundMetaheuristics.ipynb", + "title": "MGS-5 : Construire les métaheuristiques composées — des primitives au raccourci factory", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", "status": "READY", - "maturity": "BETA", - "editorial": "BETA", + "maturity": "DRAFT", + "editorial": "DRAFT", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "59f7f79fa", - "executed_at": "2026-08-31T19:49:56+02:00", + "last_success_sha": "7331d304d", + "executed_at": "2026-09-09T21:59:45+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "30min", + "duree_estimee": "45min", "owner_logique": "po-2025", - "last_validation": "2026-08-31", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#13589, #13606", - "cells_total": 23, - "cells_code": 8, - "cells_markdown": 15, - "cells_with_outputs": 5, - "cells_without_outputs": 1, + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 34, + "cells_code": 14, + "cells_markdown": 20, + "cells_with_outputs": 14, + "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, "requires_cloud": false, @@ -23790,28 +23880,28 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-14-IslandSynergyFound.ipynb", - "title": "MGS-14 — Trouver une synergie (et dire quand il n'y en a pas)", + "path": "Search/Part4-Metaheuristics/MGS-06-Benchmarks.ipynb", + "title": "MGS-6 : Benchmarks comparatifs -- l'argument primitives-based", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", "status": "READY", - "maturity": "BETA", - "editorial": "BETA", + "maturity": "ALPHA", + "editorial": "ALPHA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "59f7f79fa", - "executed_at": "2026-08-31T19:49:56+02:00", + "last_success_sha": "7331d304d", + "executed_at": "2026-09-09T21:59:45+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "owner_logique": "po-2025", - "last_validation": "2026-08-31", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#13589, #13606", - "cells_total": 19, - "cells_code": 7, - "cells_markdown": 12, - "cells_with_outputs": 4, + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 21, + "cells_code": 8, + "cells_markdown": 13, + "cells_with_outputs": 8, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -23820,8 +23910,8 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-15-LandscapeAnalysis.ipynb", - "title": "MGS-15 : Analyse de paysage -- la corrélation fitness-distance (FDC)", + "path": "Search/Part4-Metaheuristics/MGS-07-TSP.ipynb", + "title": "MGS-7 : TSP combinatoire -- la grammaire de composition est agnostique à la représentation", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", @@ -23830,18 +23920,18 @@ "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "59f7f79fa", - "executed_at": "2026-08-31T19:49:56+02:00", + "last_success_sha": "7331d304d", + "executed_at": "2026-09-09T21:59:45+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "owner_logique": "po-2025", - "last_validation": "2026-08-31", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#13589, #13606", - "cells_total": 23, - "cells_code": 10, - "cells_markdown": 13, - "cells_with_outputs": 10, + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 26, + "cells_code": 12, + "cells_markdown": 14, + "cells_with_outputs": 12, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -23850,29 +23940,29 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-16-AlgorithmSelection.ipynb", - "title": "MGS-16-AlgorithmSelection : Sélectionner le bon optimiseur selon le paysage", + "path": "Search/Part4-Metaheuristics/MGS-07b-LandscapeMultidim.ipynb", + "title": "MGS-7b : projection multi-dimensionnelle des paysages (RenderHeatmap N-D)", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", "status": "READY", - "maturity": "BETA", - "editorial": "BETA", + "maturity": "DRAFT", + "editorial": "DRAFT", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "59f7f79fa", - "executed_at": "2026-08-31T19:49:56+02:00", + "last_success_sha": "7331d304d", + "executed_at": "2026-09-09T21:59:45+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "45min", + "duree_estimee": "30min", "owner_logique": "po-2025", - "last_validation": "2026-08-31", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#13589, #13606", - "cells_total": 35, - "cells_code": 14, - "cells_markdown": 21, - "cells_with_outputs": 13, - "cells_without_outputs": 1, + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 16, + "cells_code": 8, + "cells_markdown": 8, + "cells_with_outputs": 8, + "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, "requires_cloud": false, @@ -23880,28 +23970,28 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-17-ParameterControl.ipynb", - "title": "MGS-17 — Contrôle de paramètres (Parameter Control)", + "path": "Search/Part4-Metaheuristics/MGS-07c-RosenbrockGriewank.ipynb", + "title": "MGS-7c : Rosenbrock (vallée étroite) + Griewank (produit-cosinus) en projection N-D", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", "status": "READY", - "maturity": "BETA", - "editorial": "BETA", + "maturity": "DRAFT", + "editorial": "DRAFT", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "59f7f79fa", - "executed_at": "2026-08-31T19:49:56+02:00", + "last_success_sha": "7331d304d", + "executed_at": "2026-09-09T21:59:45+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "45min", + "duree_estimee": "30min", "owner_logique": "po-2025", - "last_validation": "2026-08-31", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#13589, #13606", - "cells_total": 25, - "cells_code": 11, - "cells_markdown": 14, - "cells_with_outputs": 11, + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 14, + "cells_code": 6, + "cells_markdown": 8, + "cells_with_outputs": 6, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -23910,27 +24000,27 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-17b-Empirical-Algorithm-Selection.ipynb", - "title": "MGS-17b — Selection empirique d'algorithmes : du podium a la carte probleme x representation x solveur", + "path": "Search/Part4-Metaheuristics/MGS-07d-MichalewiczDixonPrice.ipynb", + "title": "MGS-7d : Michalewicz (steep ridges) + Dixon-Price (narrow valley non-scalable) en projection N-D", "serie": "Search", "sous_serie": "Part4-Metaheuristics", - "kernel": "Python 3 (ipykernel)", + "kernel": ".NET (C#)", "status": "READY", - "maturity": "DRAFT", - "editorial": "DRAFT", + "maturity": "BETA", + "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "67bc47b57", - "executed_at": "2026-09-02T07:51:15+02:00", + "last_success_sha": "7331d304d", + "executed_at": "2026-09-09T21:59:45+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "owner_logique": "po-2025", - "last_validation": "2026-09-02", - "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#1203, #14193", - "cells_total": 18, - "cells_code": 9, - "cells_markdown": 9, + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 14, + "cells_code": 6, + "cells_markdown": 8, "cells_with_outputs": 6, "cells_without_outputs": 0, "requires_api": false, @@ -23940,8 +24030,8 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-18-CecBanc.ipynb", - "title": "MGS-18 — Banc CEC consolide : la combinaison des deux biais", + "path": "Search/Part4-Metaheuristics/MGS-08-LandscapeExplorer.ipynb", + "title": "MGS-8 : Fitness Landscape Explorer -- voir la surface pour comprendre la recherche", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", @@ -23950,18 +24040,18 @@ "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "3cd24e354", - "executed_at": "2026-09-07T04:39:30+02:00", + "last_success_sha": "7331d304d", + "executed_at": "2026-09-09T21:59:45+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "owner_logique": "po-2025", - "last_validation": "2026-09-07", - "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#1203, #14984", - "cells_total": 29, - "cells_code": 11, - "cells_markdown": 18, - "cells_with_outputs": 11, + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 37, + "cells_code": 17, + "cells_markdown": 20, + "cells_with_outputs": 17, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -23970,8 +24060,8 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-19-MetropolisReinsertion.ipynb", - "title": "MGS-19 — Recuit simulé décomposé : l'opérateur de Metropolis isolé", + "path": "Search/Part4-Metaheuristics/MGS-09-EverestRelief.ipynb", + "title": "MGS-9 - Trouver l'Everest : relief reel et bassins d'attraction", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", @@ -23980,18 +24070,18 @@ "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "be4b581f8", - "executed_at": "2026-08-23T13:53:51+02:00", + "last_success_sha": "7331d304d", + "executed_at": "2026-09-09T21:59:45+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "30min", + "duree_estimee": "45min", "owner_logique": "po-2025", - "last_validation": "2026-08-23", - "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#1203, #12573", - "cells_total": 25, - "cells_code": 9, + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 28, + "cells_code": 12, "cells_markdown": 16, - "cells_with_outputs": 9, + "cells_with_outputs": 12, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -24000,8 +24090,8 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-2-Composition.ipynb", - "title": "MGS-2 : Composition de métaheuristiques -- Match et primitives de contrôle", + "path": "Search/Part4-Metaheuristics/MGS-10-CenterBias.ipynb", + "title": "MGS-10 : Le test du biais central — un optimiseur « sans biais en zéro » passe-t-il l'épreuve du déplacement ?", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", @@ -24010,18 +24100,18 @@ "editorial": "ALPHA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "5473ea04b", - "executed_at": "2026-08-20T18:25:30+02:00", + "last_success_sha": "59f7f79fa", + "executed_at": "2026-08-31T19:49:56+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "45min", + "duree_estimee": "30min", "owner_logique": "po-2025", - "last_validation": "2026-08-20", - "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#1203, #11943", - "cells_total": 29, - "cells_code": 11, - "cells_markdown": 18, - "cells_with_outputs": 11, + "last_validation": "2026-08-31", + "last_validator": "jessynoo@gmail.com", + "issue_pr_associee": "#13589, #13606", + "cells_total": 19, + "cells_code": 8, + "cells_markdown": 11, + "cells_with_outputs": 8, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -24030,28 +24120,28 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-20-Langage-de-Composition.ipynb", - "title": "MGS-20 : Langage de composition pour métaheuristiques", + "path": "Search/Part4-Metaheuristics/MGS-11-IslandSynergy.ipynb", + "title": "MGS-11 : Synergie d'iles complementaires -- exploration et exploitation ensemble", "serie": "Search", "sous_serie": "Part4-Metaheuristics", - "kernel": "Python 3", + "kernel": ".NET (C#)", "status": "READY", "maturity": "BETA", "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "d715f8374", - "executed_at": "2026-09-03T22:01:55+02:00", + "last_success_sha": "59f7f79fa", + "executed_at": "2026-08-31T19:49:56+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "owner_logique": "po-2025", - "last_validation": "2026-09-03", - "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14166", - "cells_total": 27, - "cells_code": 10, - "cells_markdown": 17, - "cells_with_outputs": 10, + "last_validation": "2026-08-31", + "last_validator": "jessynoo@gmail.com", + "issue_pr_associee": "#13589, #13606", + "cells_total": 16, + "cells_code": 7, + "cells_markdown": 9, + "cells_with_outputs": 7, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -24060,28 +24150,28 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-21-Representation-vs-Algorithme.ipynb", - "title": "MGS-21 : Représentation contre algorithme — la preuve croisée", + "path": "Search/Part4-Metaheuristics/MGS-12-AxisAlignment.ipynb", + "title": "MGS-12 : Le test de l'alignement d'axes -- un optimiseur résiste-t-il à la rotation du paysage ?", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", "status": "READY", - "maturity": "BETA", - "editorial": "BETA", + "maturity": "ALPHA", + "editorial": "ALPHA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "e8fe280e7", - "executed_at": "2026-08-30T00:21:16+02:00", + "last_success_sha": "59f7f79fa", + "executed_at": "2026-08-31T19:49:56+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "30min", + "duree_estimee": "45min", "owner_logique": "po-2025", - "last_validation": "2026-08-30", - "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#13515, #13526", - "cells_total": 19, - "cells_code": 9, - "cells_markdown": 10, - "cells_with_outputs": 9, + "last_validation": "2026-08-31", + "last_validator": "jessynoo@gmail.com", + "issue_pr_associee": "#13589, #13606", + "cells_total": 27, + "cells_code": 10, + "cells_markdown": 17, + "cells_with_outputs": 10, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -24090,8 +24180,8 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-3-Eukaryote.ipynb", - "title": "MGS-3 : L'Eukaryote -- sous-populations et chromosomes composites", + "path": "Search/Part4-Metaheuristics/MGS-13-LandscapeDebias.ipynb", + "title": "MGS-13 — Visualiser les paysages dé-biaisés : pourquoi la rotation casse la séparabilité", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", @@ -24100,19 +24190,19 @@ "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "9fb190c6c", - "executed_at": "2026-08-21T07:09:45+02:00", + "last_success_sha": "59f7f79fa", + "executed_at": "2026-08-31T19:49:56+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "45min", + "duree_estimee": "30min", "owner_logique": "po-2025", - "last_validation": "2026-08-21", - "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#1203, #12070", - "cells_total": 28, - "cells_code": 10, - "cells_markdown": 18, - "cells_with_outputs": 10, - "cells_without_outputs": 0, + "last_validation": "2026-08-31", + "last_validator": "jessynoo@gmail.com", + "issue_pr_associee": "#13589, #13606", + "cells_total": 23, + "cells_code": 8, + "cells_markdown": 15, + "cells_with_outputs": 5, + "cells_without_outputs": 1, "requires_api": false, "requires_gpu": false, "requires_cloud": false, @@ -24120,8 +24210,8 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-4-Islands.ipynb", - "title": "MGS-4 : Le Modèle Insulaire -- populations structurees et migration", + "path": "Search/Part4-Metaheuristics/MGS-14-IslandSynergyFound.ipynb", + "title": "MGS-14 — Trouver une synergie (et dire quand il n'y en a pas)", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", @@ -24133,15 +24223,15 @@ "last_success_sha": "59f7f79fa", "executed_at": "2026-08-31T19:49:56+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "45min", + "duree_estimee": "30min", "owner_logique": "po-2025", "last_validation": "2026-08-31", "last_validator": "jessynoo@gmail.com", "issue_pr_associee": "#13589, #13606", - "cells_total": 36, - "cells_code": 13, - "cells_markdown": 23, - "cells_with_outputs": 13, + "cells_total": 19, + "cells_code": 7, + "cells_markdown": 12, + "cells_with_outputs": 4, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -24150,28 +24240,28 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-5-CompoundMetaheuristics.ipynb", - "title": "MGS-5 : Construire les métaheuristiques composées — des primitives au raccourci factory", + "path": "Search/Part4-Metaheuristics/MGS-15-LandscapeAnalysis.ipynb", + "title": "MGS-15 : Analyse de paysage -- la corrélation fitness-distance (FDC)", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", "status": "READY", - "maturity": "DRAFT", - "editorial": "DRAFT", + "maturity": "BETA", + "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "53f6d3d67", - "executed_at": "2026-09-02T04:56:01+02:00", + "last_success_sha": "59f7f79fa", + "executed_at": "2026-08-31T19:49:56+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "45min", "owner_logique": "po-2025", - "last_validation": "2026-09-02", - "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#13777, #13959", - "cells_total": 34, - "cells_code": 14, - "cells_markdown": 20, - "cells_with_outputs": 14, + "last_validation": "2026-08-31", + "last_validator": "jessynoo@gmail.com", + "issue_pr_associee": "#13589, #13606", + "cells_total": 23, + "cells_code": 10, + "cells_markdown": 13, + "cells_with_outputs": 10, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -24180,29 +24270,29 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-6-Benchmarks.ipynb", - "title": "MGS-6 : Benchmarks comparatifs -- l'argument primitives-based", + "path": "Search/Part4-Metaheuristics/MGS-16-AlgorithmSelection.ipynb", + "title": "MGS-16-AlgorithmSelection : Sélectionner le bon optimiseur selon le paysage", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", "status": "READY", - "maturity": "ALPHA", - "editorial": "ALPHA", + "maturity": "BETA", + "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "0c2c62e49", - "executed_at": "2026-08-22T01:31:18+02:00", + "last_success_sha": "59f7f79fa", + "executed_at": "2026-08-31T19:49:56+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "30min", + "duree_estimee": "45min", "owner_logique": "po-2025", - "last_validation": "2026-08-22", - "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#1203, #12190", - "cells_total": 21, - "cells_code": 8, - "cells_markdown": 13, - "cells_with_outputs": 8, - "cells_without_outputs": 0, + "last_validation": "2026-08-31", + "last_validator": "jessynoo@gmail.com", + "issue_pr_associee": "#13589, #13606", + "cells_total": 35, + "cells_code": 14, + "cells_markdown": 21, + "cells_with_outputs": 13, + "cells_without_outputs": 1, "requires_api": false, "requires_gpu": false, "requires_cloud": false, @@ -24210,8 +24300,8 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-7-TSP.ipynb", - "title": "MGS-7 : TSP combinatoire -- la grammaire de composition est agnostique à la représentation", + "path": "Search/Part4-Metaheuristics/MGS-17-ParameterControl.ipynb", + "title": "MGS-17 — Contrôle de paramètres (Parameter Control)", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", @@ -24228,10 +24318,10 @@ "last_validation": "2026-08-31", "last_validator": "jessynoo@gmail.com", "issue_pr_associee": "#13589, #13606", - "cells_total": 26, - "cells_code": 12, + "cells_total": 25, + "cells_code": 11, "cells_markdown": 14, - "cells_with_outputs": 12, + "cells_with_outputs": 11, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -24240,28 +24330,28 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-7b-LandscapeMultidim.ipynb", - "title": "MGS-7b : projection multi-dimensionnelle des paysages (RenderHeatmap N-D)", + "path": "Search/Part4-Metaheuristics/MGS-17b-Empirical-Algorithm-Selection.ipynb", + "title": "MGS-17b — Selection empirique d'algorithmes : du podium a la carte probleme x representation x solveur", "serie": "Search", "sous_serie": "Part4-Metaheuristics", - "kernel": ".NET (C#)", + "kernel": "Python 3 (ipykernel)", "status": "READY", "maturity": "DRAFT", "editorial": "DRAFT", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "aaf552db8", - "executed_at": "2026-08-30T18:50:20+02:00", + "last_success_sha": "67bc47b57", + "executed_at": "2026-09-02T07:51:15+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "owner_logique": "po-2025", - "last_validation": "2026-08-30", + "last_validation": "2026-09-02", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#13515, #13525", - "cells_total": 16, - "cells_code": 8, - "cells_markdown": 8, - "cells_with_outputs": 8, + "issue_pr_associee": "#1203, #14193", + "cells_total": 18, + "cells_code": 9, + "cells_markdown": 9, + "cells_with_outputs": 6, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -24270,28 +24360,28 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-7c-RosenbrockGriewank.ipynb", - "title": "MGS-7c : Rosenbrock (vallée étroite) + Griewank (produit-cosinus) en projection N-D", + "path": "Search/Part4-Metaheuristics/MGS-18-CecBanc.ipynb", + "title": "MGS-18 — Banc CEC consolide : la combinaison des deux biais", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", "status": "READY", - "maturity": "DRAFT", - "editorial": "DRAFT", + "maturity": "BETA", + "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "065733c50", - "executed_at": "2026-09-05T04:01:40+02:00", + "last_success_sha": "3cd24e354", + "executed_at": "2026-09-07T04:39:30+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "30min", + "duree_estimee": "45min", "owner_logique": "po-2025", - "last_validation": "2026-09-05", + "last_validation": "2026-09-07", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14642", - "cells_total": 14, - "cells_code": 6, - "cells_markdown": 8, - "cells_with_outputs": 6, + "issue_pr_associee": "#1203, #14984", + "cells_total": 29, + "cells_code": 11, + "cells_markdown": 18, + "cells_with_outputs": 11, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -24300,8 +24390,8 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-7d-MichalewiczDixonPrice.ipynb", - "title": "MGS-7d : Michalewicz (steep ridges) + Dixon-Price (narrow valley non-scalable) en projection N-D", + "path": "Search/Part4-Metaheuristics/MGS-19-MetropolisReinsertion.ipynb", + "title": "MGS-19 — Recuit simulé décomposé : l'opérateur de Metropolis isolé", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", @@ -24310,18 +24400,18 @@ "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "61a88dc10", - "executed_at": "2026-09-04T01:52:19+02:00", + "last_success_sha": "be4b581f8", + "executed_at": "2026-08-23T13:53:51+02:00", "forensic_category": "A_ALL_EXEC_OK", "duree_estimee": "30min", "owner_logique": "po-2025", - "last_validation": "2026-09-04", + "last_validation": "2026-08-23", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#1203, #14506", - "cells_total": 14, - "cells_code": 6, - "cells_markdown": 8, - "cells_with_outputs": 6, + "issue_pr_associee": "#1203, #12573", + "cells_total": 25, + "cells_code": 9, + "cells_markdown": 16, + "cells_with_outputs": 9, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -24330,28 +24420,28 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-8-LandscapeExplorer.ipynb", - "title": "MGS-8 : Fitness Landscape Explorer -- voir la surface pour comprendre la recherche", + "path": "Search/Part4-Metaheuristics/MGS-20-Langage-de-Composition.ipynb", + "title": "MGS-20 : Langage de composition pour métaheuristiques", "serie": "Search", "sous_serie": "Part4-Metaheuristics", - "kernel": ".NET (C#)", + "kernel": "Python 3", "status": "READY", "maturity": "BETA", "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "59f7f79fa", - "executed_at": "2026-08-31T19:49:56+02:00", + "last_success_sha": "d715f8374", + "executed_at": "2026-09-03T22:01:55+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "45min", + "duree_estimee": "30min", "owner_logique": "po-2025", - "last_validation": "2026-08-31", - "last_validator": "jessynoo@gmail.com", - "issue_pr_associee": "#13589, #13606", - "cells_total": 37, - "cells_code": 17, - "cells_markdown": 20, - "cells_with_outputs": 17, + "last_validation": "2026-09-03", + "last_validator": "jsboige@gmail.com", + "issue_pr_associee": "#14166", + "cells_total": 30, + "cells_code": 13, + "cells_markdown": 17, + "cells_with_outputs": 10, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -24360,8 +24450,8 @@ "executable_locally": true }, { - "path": "Search/Part4-Metaheuristics/MGS-9-EverestRelief.ipynb", - "title": "MGS-9 - Trouver l'Everest : relief reel et bassins d'attraction", + "path": "Search/Part4-Metaheuristics/MGS-21-Representation-vs-Algorithme.ipynb", + "title": "MGS-21 : Représentation contre algorithme — la preuve croisée", "serie": "Search", "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", @@ -24370,18 +24460,18 @@ "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", - "last_success_sha": "065733c50", - "executed_at": "2026-09-05T04:01:40+02:00", + "last_success_sha": "e8fe280e7", + "executed_at": "2026-08-30T00:21:16+02:00", "forensic_category": "A_ALL_EXEC_OK", - "duree_estimee": "45min", + "duree_estimee": "30min", "owner_logique": "po-2025", - "last_validation": "2026-09-05", + "last_validation": "2026-08-30", "last_validator": "jsboige@gmail.com", - "issue_pr_associee": "#14642", - "cells_total": 28, - "cells_code": 12, - "cells_markdown": 16, - "cells_with_outputs": 12, + "issue_pr_associee": "#13515, #13526", + "cells_total": 19, + "cells_code": 9, + "cells_markdown": 10, + "cells_with_outputs": 9, "cells_without_outputs": 0, "requires_api": false, "requires_gpu": false, @@ -24636,8 +24726,8 @@ "sous_serie": "Part4-Metaheuristics", "kernel": ".NET (C#)", "status": "READY", - "maturity": "DRAFT", - "editorial": "DRAFT", + "maturity": "BETA", + "editorial": "BETA", "reproducibility": "EXECUTED", "scientific_review": "UNREVIEWED", "last_success_sha": "53f6d3d67", @@ -24648,9 +24738,9 @@ "last_validation": "2026-09-02", "last_validator": "jsboige@gmail.com", "issue_pr_associee": "#13777, #13959", - "cells_total": 21, + "cells_total": 23, "cells_code": 10, - "cells_markdown": 11, + "cells_markdown": 13, "cells_with_outputs": 10, "cells_without_outputs": 0, "requires_api": false, @@ -25614,10 +25704,10 @@ "last_validation": "2026-08-31", "last_validator": "jessynoo@gmail.com", "issue_pr_associee": "#13589, #13606", - "cells_total": 63, - "cells_code": 26, - "cells_markdown": 37, - "cells_with_outputs": 20, + "cells_total": 65, + "cells_code": 27, + "cells_markdown": 38, + "cells_with_outputs": 21, "cells_without_outputs": 4, "requires_api": false, "requires_gpu": false, @@ -27938,6 +28028,66 @@ "requires_wsl": true, "executable_locally": false }, + { + "path": "SymbolicAI/Lean/Lean-31-Hecke-Operators-Native.ipynb", + "title": "Lean-31 : les opérateurs de Hecke $T_p$ et $U_p$ — compagnon natif du lake hecke_lean", + "serie": "SymbolicAI", + "sous_serie": "Lean", + "kernel": "Lean 4 (WSL)", + "status": "READY", + "maturity": "BETA", + "editorial": "BETA", + "reproducibility": "EXECUTED", + "scientific_review": "UNREVIEWED", + "last_success_sha": "040744e72", + "executed_at": "2026-09-09T12:36:25+02:00", + "forensic_category": "A_ALL_EXEC_OK", + "duree_estimee": "30min", + "owner_logique": "po-2024", + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 32, + "cells_code": 11, + "cells_markdown": 21, + "cells_with_outputs": 11, + "cells_without_outputs": 0, + "requires_api": false, + "requires_gpu": false, + "requires_cloud": false, + "requires_wsl": true, + "executable_locally": false + }, + { + "path": "SymbolicAI/Lean/Lean-32-FormalGroups-Native.ipynb", + "title": "Lean-32 : groupes formels multivariés — compagnon natif", + "serie": "SymbolicAI", + "sous_serie": "Lean", + "kernel": "Lean 4 (WSL)", + "status": "READY", + "maturity": "BETA", + "editorial": "BETA", + "reproducibility": "EXECUTED", + "scientific_review": "UNREVIEWED", + "last_success_sha": "48a9a18d6", + "executed_at": "2026-09-08T14:33:47+02:00", + "forensic_category": "A_ALL_EXEC_OK", + "duree_estimee": "30min", + "owner_logique": "po-2024", + "last_validation": "", + "last_validator": "", + "issue_pr_associee": "", + "cells_total": 33, + "cells_code": 11, + "cells_markdown": 22, + "cells_with_outputs": 6, + "cells_without_outputs": 0, + "requires_api": false, + "requires_gpu": false, + "requires_cloud": false, + "requires_wsl": true, + "executable_locally": false + }, { "path": "SymbolicAI/Lean/Lean-4-Quantifiers.ipynb", "title": "Lean 4 - Quantificateurs et Logique du Premier Ordre", @@ -31360,7 +31510,7 @@ }, { "path": "SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-10-Account-Abstraction.ipynb", - "title": "SC-10-Account-Abstraction - ERC-4337", + "title": "SC-10-Account-Abstraction - ERC-4337 v0.9", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", @@ -31390,11 +31540,11 @@ }, { "path": "SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-11-LLM-Assisted.ipynb", - "title": "SC-11-LLM-Assisted - Développement Smart Contracts Assiste par LLM", + "title": "SC-11-LLM-Assisted - Développement Smart Contracts Assisté par LLM", "serie": "SymbolicAI", "sous_serie": "SmartContracts", "kernel": "Python 3", - "status": "DEMO", + "status": "READY", "maturity": "BETA", "editorial": "BETA", "reproducibility": "EXECUTED", @@ -31410,7 +31560,7 @@ "cells_total": 52, "cells_code": 20, "cells_markdown": 32, - "cells_with_outputs": 15, + "cells_with_outputs": 16, "cells_without_outputs": 0, "requires_api": true, "requires_gpu": false, diff --git a/COURSE_CATALOG.generated.md b/COURSE_CATALOG.generated.md index ea3e46ce0c..e4a71271af 100644 --- a/COURSE_CATALOG.generated.md +++ b/COURSE_CATALOG.generated.md @@ -1,22 +1,22 @@ # CoursIA Notebook Catalog -Generated: 2026-09-08 08:44 -Total notebooks: 1125 +Generated: 2026-09-10 08:25 +Total notebooks: 1130 ## Status Summary -- **READY**: 947 -- **DEMO**: 175 +- **READY**: 953 +- **DEMO**: 174 - **RESEARCH**: 0 - **BROKEN**: 2 ## Maturity Summary - **PRODUCTION**: 0 -- **BETA**: 993 +- **BETA**: 998 - **TEMPLATE**: 4 -- **ALPHA**: 57 -- **DRAFT**: 71 +- **ALPHA**: 58 +- **DRAFT**: 70 ## By Series @@ -240,7 +240,7 @@ Total notebooks: 1125 | 214 | MiniMax H3 (Hailuo) — Génération vidéo par le… | Python 3 | DEMO | BETA | 30min | po-2025 | | 215 | MiniMax video-01 (v1) — Service cloud generation… | Python 3 | DEMO | BETA | 30min | po-2025 | -### Search (149 notebooks) — READY:149 | ALPHA:10, BETA:133, DRAFT:6 +### Search (149 notebooks) — READY:149 | ALPHA:10, BETA:134, DRAFT:5 | # | Notebook | Kernel | Status | Maturity | Duration | Owner | |---|----------|--------|--------|----------|----------|-------| @@ -359,30 +359,30 @@ Total notebooks: 1125 | 113 | CSP-9-Distributed | .NET (C#) | READY | BETA | 45min | po-2025 | | 114 | CSP-9-Distributed : CSP Distribués (DisCSP) | Python 3 | READY | BETA | 45min | po-2025 | | 115 | MGS-1 : Introduction a MetaGeneticSharp et au… | .NET (C#) | READY | BETA | 30min | po-2025 | -| 116 | MGS-10 : Le test du biais central — un optimiseur… | .NET (C#) | READY | ALPHA | 30min | po-2025 | -| 117 | MGS-11 : Synergie d'iles complementaires --… | .NET (C#) | READY | BETA | 30min | po-2025 | -| 118 | MGS-12 : Le test de l'alignement d'axes -- un… | .NET (C#) | READY | ALPHA | 45min | po-2025 | -| 119 | MGS-13 — Visualiser les paysages dé-biaisés :… | .NET (C#) | READY | BETA | 30min | po-2025 | -| 120 | MGS-14 — Trouver une synergie (et dire quand il… | .NET (C#) | READY | BETA | 30min | po-2025 | -| 121 | MGS-15 : Analyse de paysage -- la corrélation… | .NET (C#) | READY | BETA | 45min | po-2025 | -| 122 | MGS-16-AlgorithmSelection : Sélectionner le bon… | .NET (C#) | READY | BETA | 45min | po-2025 | -| 123 | MGS-17 — Contrôle de paramètres (Parameter… | .NET (C#) | READY | BETA | 45min | po-2025 | -| 124 | MGS-17b — Selection empirique d'algorithmes : du… | Python 3 (ipykernel) | READY | DRAFT | 30min | po-2025 | -| 125 | MGS-18 — Banc CEC consolide : la combinaison des… | .NET (C#) | READY | BETA | 45min | po-2025 | -| 126 | MGS-19 — Recuit simulé décomposé : l'opérateur de… | .NET (C#) | READY | BETA | 30min | po-2025 | -| 127 | MGS-2 : Composition de métaheuristiques -- Match… | .NET (C#) | READY | ALPHA | 45min | po-2025 | -| 128 | MGS-20 : Langage de composition pour… | Python 3 | READY | BETA | 30min | po-2025 | -| 129 | MGS-21 : Représentation contre algorithme — la… | .NET (C#) | READY | BETA | 30min | po-2025 | -| 130 | MGS-3 : L'Eukaryote -- sous-populations et… | .NET (C#) | READY | BETA | 45min | po-2025 | -| 131 | MGS-4 : Le Modèle Insulaire -- populations… | .NET (C#) | READY | BETA | 45min | po-2025 | -| 132 | MGS-5 : Construire les métaheuristiques composées… | .NET (C#) | READY | DRAFT | 45min | po-2025 | -| 133 | MGS-6 : Benchmarks comparatifs -- l'argument… | .NET (C#) | READY | ALPHA | 30min | po-2025 | -| 134 | MGS-7 : TSP combinatoire -- la grammaire de… | .NET (C#) | READY | BETA | 45min | po-2025 | -| 135 | MGS-7b : projection multi-dimensionnelle des… | .NET (C#) | READY | DRAFT | 30min | po-2025 | -| 136 | MGS-7c : Rosenbrock (vallée étroite) + Griewank… | .NET (C#) | READY | DRAFT | 30min | po-2025 | -| 137 | MGS-7d : Michalewicz (steep ridges) + Dixon-Price… | .NET (C#) | READY | BETA | 30min | po-2025 | -| 138 | MGS-8 : Fitness Landscape Explorer -- voir la… | .NET (C#) | READY | BETA | 45min | po-2025 | -| 139 | MGS-9 - Trouver l'Everest : relief reel et bassins… | .NET (C#) | READY | BETA | 45min | po-2025 | +| 116 | MGS-2 : Composition de métaheuristiques -- Match… | .NET (C#) | READY | ALPHA | 45min | po-2025 | +| 117 | MGS-3 : L'Eukaryote -- sous-populations et… | .NET (C#) | READY | BETA | 45min | po-2025 | +| 118 | MGS-4 : Le Modèle Insulaire -- populations… | .NET (C#) | READY | BETA | 45min | po-2025 | +| 119 | MGS-5 : Construire les métaheuristiques composées… | .NET (C#) | READY | DRAFT | 45min | po-2025 | +| 120 | MGS-6 : Benchmarks comparatifs -- l'argument… | .NET (C#) | READY | ALPHA | 30min | po-2025 | +| 121 | MGS-7 : TSP combinatoire -- la grammaire de… | .NET (C#) | READY | BETA | 45min | po-2025 | +| 122 | MGS-7b : projection multi-dimensionnelle des… | .NET (C#) | READY | DRAFT | 30min | po-2025 | +| 123 | MGS-7c : Rosenbrock (vallée étroite) + Griewank… | .NET (C#) | READY | DRAFT | 30min | po-2025 | +| 124 | MGS-7d : Michalewicz (steep ridges) + Dixon-Price… | .NET (C#) | READY | BETA | 30min | po-2025 | +| 125 | MGS-8 : Fitness Landscape Explorer -- voir la… | .NET (C#) | READY | BETA | 45min | po-2025 | +| 126 | MGS-9 - Trouver l'Everest : relief reel et bassins… | .NET (C#) | READY | BETA | 45min | po-2025 | +| 127 | MGS-10 : Le test du biais central — un optimiseur… | .NET (C#) | READY | ALPHA | 30min | po-2025 | +| 128 | MGS-11 : Synergie d'iles complementaires --… | .NET (C#) | READY | BETA | 30min | po-2025 | +| 129 | MGS-12 : Le test de l'alignement d'axes -- un… | .NET (C#) | READY | ALPHA | 45min | po-2025 | +| 130 | MGS-13 — Visualiser les paysages dé-biaisés :… | .NET (C#) | READY | BETA | 30min | po-2025 | +| 131 | MGS-14 — Trouver une synergie (et dire quand il… | .NET (C#) | READY | BETA | 30min | po-2025 | +| 132 | MGS-15 : Analyse de paysage -- la corrélation… | .NET (C#) | READY | BETA | 45min | po-2025 | +| 133 | MGS-16-AlgorithmSelection : Sélectionner le bon… | .NET (C#) | READY | BETA | 45min | po-2025 | +| 134 | MGS-17 — Contrôle de paramètres (Parameter… | .NET (C#) | READY | BETA | 45min | po-2025 | +| 135 | MGS-17b — Selection empirique d'algorithmes : du… | Python 3 (ipykernel) | READY | DRAFT | 30min | po-2025 | +| 136 | MGS-18 — Banc CEC consolide : la combinaison des… | .NET (C#) | READY | BETA | 45min | po-2025 | +| 137 | MGS-19 — Recuit simulé décomposé : l'opérateur de… | .NET (C#) | READY | BETA | 30min | po-2025 | +| 138 | MGS-20 : Langage de composition pour… | Python 3 | READY | BETA | 30min | po-2025 | +| 139 | MGS-21 : Représentation contre algorithme — la… | .NET (C#) | READY | BETA | 30min | po-2025 | | 140 | MGS-22 : MGS contre mealpy — le bench croisé… | .NET (C#) | READY | BETA | 45min | po-2025 | | 141 | MGS-23 : DifferentialEvolution MGS contre mealpy —… | .NET (C#) | READY | BETA | 45min | po-2025 | | 142 | MGS-24 : SimulatedAnnealing MGS contre mealpy —… | .NET (C#) | READY | ALPHA | 30min | po-2025 | @@ -391,7 +391,7 @@ Total notebooks: 1125 | 145 | MGS-27 : ForensicBasedInvestigation MGS contre… | .NET (C#) | READY | ALPHA | 30min | po-2025 | | 146 | MGS-28 : Bare Bones PSO MGS contre mealpy — le PSO… | .NET (C#) | READY | ALPHA | 45min | po-2025 | | 147 | MGS-29 : GA MGS compose "Default" contre BaseGA… | .NET (C#) | READY | BETA | 30min | po-2025 | -| 148 | MGS-30 : Scatter Search MGS contre son ombre — la… | .NET (C#) | READY | DRAFT | 45min | po-2025 | +| 148 | MGS-30 : Scatter Search MGS contre son ombre — la… | .NET (C#) | READY | BETA | 45min | po-2025 | | 149 | MGS-31 : Synthèse croisée MGS contre mealpy — neuf… | .NET (C#) | READY | DRAFT | 30min | po-2025 | ### ML (81 notebooks) — DEMO:7, READY:74 | ALPHA:5, BETA:75, DRAFT:1 @@ -480,7 +480,7 @@ Total notebooks: 1125 | 80 | ML-9 : Detection d'anomalies avec Randomized PCA | .NET (C#) | READY | BETA | 45min | po-2023 | | 81 | TP : Prevision des ventes d'assurance | .NET (C#) | READY | BETA | 30min | po-2023 | -### SymbolicAI (263 notebooks) — DEMO:8, READY:255 | ALPHA:6, BETA:253, DRAFT:4 +### SymbolicAI (265 notebooks) — DEMO:7, READY:258 | ALPHA:6, BETA:255, DRAFT:4 | # | Notebook | Kernel | Status | Maturity | Duration | Owner | |---|----------|--------|--------|----------|----------|-------| @@ -554,199 +554,201 @@ Total notebooks: 1125 | 68 | Lean-29 : coloration d'arêtes et conjecture de… | Lean 4 (WSL) | READY | BETA | 15min | po-2024 | | 69 | Lean 3 - Propositions et Preuves | Lean 4 | READY | BETA | 45min | po-2024 | | 70 | Lean-30 : Le problème de Hopf sur S⁶ — digestion… | Python 3 | READY | BETA | 30min | po-2024 | -| 71 | Lean 4 - Quantificateurs et Logique du Premier… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | -| 72 | Lean 5 - Mode Tactique | Lean 4 | READY | BETA | 1h | po-2024 | -| 73 | Lean 6 - Mathlib4 : La Bibliotheque Mathematique | Lean 4 | READY | BETA | 45min | po-2024 | -| 74 | Lean 7 - Integration des LLMs pour l'Assistance… | Python 3 (WSL) | READY | BETA | 45min | po-2024 | -| 75 | Lean 7b - Exemples Progressifs et Benchmarks | Python 3 (WSL) | READY | BETA | 30min | po-2024 | -| 76 | Lean 8 - Agents Autonomes pour Demonstration de… | Python 3 | READY | BETA | 30min | po-2024 | -| 77 | Lean 9 : Multi-Agents avec Semantic Kernel | Python 3 | READY | BETA | 45min | po-2024 | -| 78 | Configuration de l'environnement C# | .NET (C#) | READY | BETA | 45min | po-2024 | -| 79 | Planners-0-Setup | Python 3 | READY | BETA | 30min | po-2024 | -| 80 | Planners-1-Introduction-Csharp : la planification… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 81 | Planners-1-Introduction a la Planification… | Python 3 | READY | BETA | 30min | po-2024 | -| 82 | Planners-2-PDDL-Basics-Csharp | .NET (C#) | READY | BETA | 45min | po-2024 | -| 83 | Planners-2-PDDL-Basics | Python 3 | READY | BETA | 30min | po-2024 | -| 84 | Planners-3 : Recherche dans l'Espace d'Etats —… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 85 | Planners-3-State-Space - Recherche dans l'Espace… | Python 3 | READY | BETA | 45min | po-2024 | -| 86 | Planners-4-Fast-Downward (C#) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 87 | Planners-4-Fast-Downward - Planificateur Classique | Python 3 | READY | BETA | 45min | po-2024 | -| 88 | Planners-5-Heuristics-Csharp | .NET (C#) | READY | BETA | 45min | po-2024 | -| 89 | Planners-5-Heuristiques en Planification | Python 3 | READY | BETA | 45min | po-2024 | -| 90 | Planners-5b — Admissibilité de la relaxation… | Lean 4 (WSL) | READY | BETA | 15min | po-2024 | -| 91 | Planners-5c — Le différentiel d'atteignabilité :… | Python 3 | READY | BETA | 30min | po-2024 | -| 92 | Planners-6-Domains-Csharp — Jumeau C# :… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 93 | Planners-6-Domains - Domaines Classiques de… | Python 3 | READY | BETA | 45min | po-2024 | -| 94 | Planners-7-OR-Tools-Csharp — Jumeau C# : solveur… | .NET (C#) | READY | BETA | 30min | po-2024 | -| 95 | Planners-7-OR-Tools - Programmation par… | Python 3 | READY | BETA | 45min | po-2024 | -| 96 | Planners-8-Temporal — Planification Temporelle… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 97 | Planners-8-Temporal - Planification Temporelle | Python 3 | READY | BETA | 45min | po-2024 | -| 98 | Planners-9-HTN (C#) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 99 | Planners-9-HTN - Planification Hiérarchique | Python 3 | READY | BETA | 45min | po-2024 | -| 100 | Planners-10: LLMs pour la Planification | Python 3 | READY | BETA | 45min | po-2024 | -| 101 | Planners-10b: Le LLM comme reducteur d'espace de… | Python 3 | READY | BETA | 30min | po-2024 | -| 102 | Planners-11: Unified Planning | Python 3 | READY | BETA | 45min | po-2024 | -| 103 | Planners-12: Learning to Plan avec LOOP | Python 3 | READY | BETA | 45min | po-2024 | -| 104 | Z3 (C# / .NET) — Introduction au solveur SMT | .NET (C#) | READY | BETA | 30min | po-2024 | -| 105 | Z3-Python 01 — Introduction a la resolution de… | Python 3 | READY | BETA | 30min | po-2024 | -| 106 | Z3-Python 01b — Du style declaratif LINQ au… | Python 3 | READY | BETA | 15min | po-2024 | -| 107 | Z3 (C# / .NET) — Sudoku par contraintes | .NET (C#) | READY | BETA | 30min | po-2024 | -| 108 | Z3-Python 02 — Sudoku comme problème de… | Python 3 | READY | BETA | 15min | po-2024 | -| 109 | Z3 (C# / .NET) — Tactiques, théories BitVec et… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 110 | Z3-Python 03 — Tactiques et théories | Python 3 | READY | BETA | 30min | po-2024 | -| 111 | Z3 (C# / .NET) — Théorie des chaînes et… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 112 | Z3-Python 04 — Chaînes de caractères et… | Python 3 | READY | BETA | 30min | po-2024 | -| 113 | Z3 (C# / .NET) — Quantificateurs et preuves par… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 114 | Z3-Python 05 — Quantificateurs et preuves… | Python 3 | READY | BETA | 30min | po-2024 | -| 115 | Z3-Python 06 -- Optimisation avancee (twin C#) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 116 | Z3-Python 06 — Optimisation avancee | Python 3 | READY | BETA | 30min | po-2024 | -| 117 | Z3-Python-08 : Ordonnancement de tâches (Job-Shop… | Python 3 | READY | BETA | 30min | po-2024 | -| 118 | Z3-Python-09 : L'enigme d'Einstein (Zebra puzzle) | Python 3 | READY | BETA | 15min | po-2024 | -| 119 | 10. Cryptarithmes (SEND + MORE = MONEY) | Python 3 | READY | BETA | 15min | po-2024 | -| 120 | 11 - Coloration de Graphe avec Z3 | Python 3 | READY | BETA | 30min | po-2024 | -| 121 | 12. Arithmetique reelle : raisonner sur les… | Python 3 | READY | BETA | 30min | po-2024 | -| 122 | 13. UNSAT cores : expliquer l'insatisfiabilite (le… | Python 3 | READY | BETA | 30min | po-2024 | -| 123 | 14. Bit-vectors : verifier le debordement… | Python 3 | READY | BETA | 30min | po-2024 | -| 124 | 15. Tableaux imbriqués et grilles 2D : carrés… | Python 3 | READY | BETA | 30min | po-2024 | -| 125 | 16. Meal-Planner déclaratif : du modèle Z3 au plan… | Python 3 | READY | BETA | 30min | po-2024 | -| 126 | Z3-Python-16b — Meal-Planner : couche de données… | Python 3 | READY | BETA | 30min | po-2024 | -| 127 | Z3-Python-16c — Meal-Planner : capstone patient… | Python 3 | READY | BETA | 30min | po-2024 | -| 128 | Z3-Python-16d — Convergence à l'échelle :… | Python 3 | READY | BETA | 30min | po-2024 | -| 129 | Z3-Python-16e — Meal-Planner : l'optimisation (du… | Python 3 | READY | BETA | 30min | po-2024 | -| 130 | Z3-Python 17 — Théorie des tableaux : Select,… | Python 3 | READY | BETA | 15min | po-2024 | -| 131 | Z3-Python 18 — Sudoku 4x4 : comparaison des modes… | Python 3 | READY | BETA | 15min | po-2024 | -| 132 | LINQ to Z3 - Résolution de Contraintes Déclarative | .NET (C#) | READY | BETA | 45min | po-2024 | -| 133 | Sudoku : Théorème Explicite vs Modèle Implicite… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 134 | Sudoku 4x4 : comparaison des modes Array et… | .NET (C#) | READY | BETA | 30min | po-2024 | -| 135 | Théorie des Tableaux Z3 — Select, Store et… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 136 | Tableaux Imbriqués et Grilles 2D : API Déclarative… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 137 | Notebook 06 — Meal-Planner declaratif : du modèle… | .NET (C#) | READY | BETA | 1h | po-2024 | -| 138 | 07 — Données réelles & externe : Ciqual × RecipeML… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 139 | 08 — Capstone hiérarchique : du squelette int[][]… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 140 | 09 — Convergence à l'échelle : l'encodage décide… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 141 | 10 — Générer un témoin depuis A & ~B (fork… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 142 | Notebook 11 — Ordonnancement d'atelier (Job Shop… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 143 | Notebook 12 - Coloration de graphe : le graphe de… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 144 | Notebook 13 — Cryptarithmes : l'arithmétique… | .NET (C#) | READY | BETA | 30min | po-2024 | -| 145 | Notebook 14 — De SAT à OPT : optimisation et… | .NET (C#) | READY | BETA | 30min | po-2024 | -| 146 | 15 — Théorie des bit-vectors Z3 : vérifier le… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 147 | 16 — Arithmétique réelle Z3 : raisonner sur les… | .NET (C#) | READY | DRAFT | 30min | po-2024 | -| 148 | 17 — UNSAT cores Z3 : expliquer l'insatisfiabilité… | .NET (C#) | READY | BETA | 30min | po-2024 | -| 149 | Notebook 18 - L'enigme d'Einstein : la logique des… | .NET (C#) | READY | BETA | 30min | po-2024 | -| 150 | Introduction au web sémantique avec RDF.Net | .NET (C#) | READY | BETA | 2h+ | po-2024 | -| 151 | SW-1-Setup | .NET (C#) | READY | BETA | 30min | po-2024 | -| 152 | SW-10-CSharp-RDFStar — Jumeau C# : annoter des… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 153 | SW-10-Python-RDFStar | Python 3 | READY | BETA | 45min | po-2024 | -| 154 | SW-11-CSharp-KnowledgeGraphs | .NET (C#) | READY | BETA | 45min | po-2024 | -| 155 | SW-11-Python-KnowledgeGraphs | Python 3 | READY | BETA | 1h | po-2024 | -| 156 | SW-12-Python-GraphRAG | Python 3 | DEMO | BETA | 45min | po-2024 | -| 157 | SW-13-Reasoners | Python 3 | READY | BETA | 1h | po-2024 | -| 158 | SW-13 (C#) : Raisonneurs RDF/OWL — Inferer des… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 159 | SW-14 — Le coup ontologique comme diff de graphe… | Python 3 | READY | BETA | 15min | po-2024 | -| 160 | SW-15 — Le coup argumentatif : greffer AIF sur le… | Python 3 | READY | BETA | 30min | po-2024 | -| 161 | SW-2-RDFBasics | .NET (C#) | READY | BETA | 45min | po-2024 | -| 162 | SW-2b-Python-RDFBasics | Python 3 | READY | BETA | 45min | po-2024 | -| 163 | SW-3-GraphOperations | .NET (C#) | READY | BETA | 1h | po-2024 | -| 164 | SW-3b-Python-GraphOperations | Python 3 (ipykernel) | READY | BETA | 45min | po-2024 | -| 165 | SW-4-SPARQL | .NET (C#) | READY | BETA | 45min | po-2024 | -| 166 | SW-4b-Python-SPARQL | Python 3 | READY | BETA | 45min | po-2024 | -| 167 | SW-5-LinkedData | .NET (C#) | READY | BETA | 45min | po-2024 | -| 168 | SW-5b-Python-LinkedData | .venv (3.12.3) | DEMO | BETA | 45min | po-2024 | -| 169 | SW-6-RDFS | .NET (C#) | READY | BETA | 45min | po-2024 | -| 170 | SW-6b-Python-RDFS | Python 3 (ipykernel) | READY | BETA | 30min | po-2024 | -| 171 | SW-7-OWL | .NET (C#) | READY | BETA | 45min | po-2024 | -| 172 | SW-7b-Python-OWL | Python 3 | DEMO | BETA | 45min | po-2024 | -| 173 | SW-8-CSharp-SHACL | .NET (C#) | READY | BETA | 45min | po-2024 | -| 174 | SW-8-Python-SHACL | Python 3 | READY | BETA | 45min | po-2024 | -| 175 | SW-9-CSharp-JSONLD -- JSON-LD avec dotNetRDF (twin… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 176 | SW-9-Python-JSONLD | Python 3 | READY | BETA | 1h | po-2024 | -| 177 | SC-0-Cypherpunk-Origins - Les origines Cypherpunk… | Python 3 | READY | BETA | 45min | po-2024 | -| 178 | SC-1-Setup-Foundry - Environnement Smart Contracts | Python 3 | READY | BETA | 15min | po-2024 | -| 179 | SC-2-Setup-Web3py - Python et la Blockchain | Python 3 | READY | BETA | 30min | po-2024 | -| 180 | SC-2b - Bac a sable institutionnel : des acteurs,… | Python 3 | READY | BETA | 45min | po-2024 | -| 181 | SC-3-Solidity-Basics - Fondements de Solidity | .venv | READY | BETA | 45min | po-2024 | -| 182 | SC-4-Functions-State - Fonctions et État | Python 3 | READY | BETA | 45min | po-2024 | -| 183 | SC-5-Inheritance - Heritage et Interfaces | Python 3 | READY | BETA | 30min | po-2024 | -| 184 | SC-6-Errors-Events - Erreurs et Événements | Python 3 | READY | BETA | 30min | po-2024 | -| 185 | SC-10-Account-Abstraction - ERC-4337 | Python 3 | READY | BETA | 30min | po-2024 | -| 186 | SC-11-LLM-Assisted - Développement Smart Contracts… | Python 3 | DEMO | BETA | 45min | po-2024 | -| 187 | SC-7-Token-Standards - Standards de Tokens | Python 3 | READY | BETA | 30min | po-2024 | -| 188 | SC-7b : ERC-20 + Lean — vérification formelle de… | Python3 | READY | BETA | 15min | po-2024 | -| 189 | SC-7c : ERC-20 — compagnon natif Lean (kernel… | Lean 4 (WSL) | READY | ALPHA | 30min | po-2024 | -| 190 | SC-8-DeFi-Primitives - Primitives DeFi | Python 3 | READY | BETA | 30min | po-2024 | -| 191 | SC-9-DAO-Governance - Gouvernance DAO | cours-ia | READY | BETA | 30min | po-2024 | -| 192 | SC-12-Foundry-Testing - Tests avec Foundry | Python 3 | READY | BETA | 45min | po-2024 | -| 193 | SC-13-Fuzz-Invariants - Fuzz Testing | Python 3 | READY | BETA | 30min | po-2024 | -| 194 | SC-14-Formal-Vérification - Vérification Formelle | Python 3 | DEMO | BETA | 30min | po-2024 | -| 195 | SC-15-Zero-Knowledge-Proofs - Preuves a… | Python 3 | READY | BETA | 45min | po-2024 | -| 196 | SC-16-Homomorphic-Encryption - Chiffrement… | Python 3 (SC-16 Concrete, WSL) | READY | BETA | 30min | po-2024 | -| 197 | SC-17-E2E-Verifiable-Voting - Vote Electronique… | Python 3 | READY | BETA | 30min | po-2024 | -| 198 | SC-18-Vyper - Smart Contracts en Python-like | Python 3 | READY | BETA | 30min | po-2024 | -| 199 | SC-19-Ripple-XRP - Protocole Ripple et XRP Ledger | Python 3 (smartcontracts) | READY | BETA | 30min | po-2024 | -| 200 | SC-20-Bitcoin-Scripting - Bitcoin, UTXO et Scripts | .venv | READY | BETA | 30min | po-2024 | -| 201 | SC-21-Move-Sui - Move sur Sui | Python 3 | READY | BETA | 30min | po-2024 | -| 202 | SC-22-Solana-Anchor - Solana avec Anchor | Python 3 | READY | BETA | 30min | po-2024 | -| 203 | SC-23-Cross-Chain - Interoperabilite Cross-Chain | Python 3 | READY | BETA | 30min | po-2024 | -| 204 | SC-24 : Deploiement sur Testnets | Python 3 | READY | BETA | 30min | po-2024 | -| 205 | SC-25 : Deploiement Mainnet (L2) | Python 3 | READY | BETA | 30min | po-2024 | -| 206 | SC-26 : Projet Final - DApp Complete | Python 3 | READY | BETA | 15min | po-2024 | -| 207 | SC-27 : Dette d'irréversibilité — la boucle de… | Python 3 | READY | BETA | 30min | po-2024 | -| 208 | SL-1 - Apprentissage Logique : CBH Search et… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 209 | SL-1 - Apprentissage Logique : CBH Search et… | Python 3 | READY | BETA | 45min | po-2024 | -| 210 | SL-10 --- Apprentissage Actif d'Automates (L*… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 211 | SL-10 --- Apprentissage Actif d'Automates (L*… | Python 3 | READY | BETA | 45min | po-2024 | -| 212 | SL-11 --- Capstone : un pipeline neuro-symbolique… | Python 3 | READY | BETA | 45min | po-2024 | -| 213 | SL-12 : Differentiable Logic Gate Networks | Python (difflogic-sl12) | READY | BETA | 45min | po-2024 | -| 214 | SL-12b : Synthèse logique spectrale — Fourier… | Python 3 | READY | BETA | 45min | po-2024 | -| 215 | SL-1b — Apprentissage PAC formellement : le lake… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 216 | SL-2 - Apprentissage et Connaissance : EBL & RBL… | .NET (C#) | READY | ALPHA | 45min | po-2024 | -| 217 | SL-2 --- Apprentissage et Connaissance (EBL & RBL) | Python 3 | READY | BETA | 45min | po-2024 | -| 218 | SL-3 — Apprentissage basé sur la pertinence (twin… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 219 | SL-3 --- Apprentissage Base sur la Pertinence (RBL… | Python 3 | READY | BETA | 45min | po-2024 | -| 220 | SL-4 — Programmation Logique Inductive (ILP) —… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 221 | SL-4 --- Programmation Logique Inductive (ILP) | Python 3 (WSL) | READY | BETA | 45min | po-2024 | -| 222 | SL-5 - Resolution Inverse & ILP (C#) | .NET (C#) | READY | ALPHA | 45min | po-2024 | -| 223 | SL-5 --- Resolution Inverse et Progol (ILP… | Python 3 | READY | BETA | 30min | po-2024 | -| 224 | SL-6 (C#) : Moteurs ILP modernes — apprendre des… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 225 | SL-6 --- Moteurs ILP modernes : Aleph, Metagol,… | Python 3 (WSL) | READY | BETA | 30min | po-2024 | -| 226 | SL-7 : Integration Neuro-Symbolique | Python 3 | READY | BETA | 45min | po-2024 | -| 227 | SL-8 (C#) : ILP Moderne et Knowledge Graphs | .NET (C#) | READY | BETA | 45min | po-2024 | -| 228 | SL-8 - ILP Moderne et Knowledge Graphs | Python 3 | READY | BETA | 45min | po-2024 | -| 229 | SL-9 - LLMs et Apprentissage Symbolique :… | Python 3 | READY | BETA | 45min | po-2024 | -| 230 | Configuration et Installation TweetyProject | Python 3 | READY | BETA | 45min | po-2024 | -| 231 | Tweety-10 — Markov Logic Networks (MLN) en .NET… | .NET (C#) | READY | BETA | 30min | po-2024 | -| 232 | Tweety-10 — Markov Logic Networks (MLN) | Python 3 | READY | BETA | 30min | po-2024 | -| 233 | Tweety-11 — Inférence causale & do-calculus (twin… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 234 | Tweety-11 — Raisonnement Causal : du do-calculus… | Python 3 | READY | BETA | 30min | po-2024 | -| 235 | Argumentation Abstraite : Grounded Extension -… | Python 3 | READY | BETA | 30min | po-2024 | -| 236 | Tweety C# / IKVM - Logiques de Base (Port .NET du… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 237 | Logiques de Base - Propositionnelle et Premier… | Python 3 | READY | BETA | 45min | po-2024 | -| 238 | Tweety C# / IKVM - Sémantique propositionnelle :… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 239 | Tweety-2c — Logique du premier ordre en C#/.NET… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 240 | Tweety-3 — Description Logics en C#/.NET (port… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 241 | Logiques Avancees - DL, Modale, QBF, Conditional | Python 3 | READY | BETA | 45min | po-2024 | -| 242 | Tweety-3 — Conditional Logics en C#/.NET (port… | .NET (C#) | READY | BETA | 30min | po-2024 | -| 243 | Tweety-3 — Argumentation abstraite de Dung en… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 244 | Tweety-3 Modal Logic en C#/.NET (port natif IKVM) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 245 | Tweety-3 - Quantified Boolean Formulas en C#/.NET… | .NET (C#) | READY | BETA | 30min | po-2024 | -| 246 | Tweety-4 — Argumentation structurée ASPIC+ en… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 247 | Tweety C# / IKVM - Revision de Croyances (Port… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 248 | Révision de Croyances et Incohérence | Python 3 | READY | BETA | 30min | po-2024 | -| 249 | Tweety-5 : Argumentation Abstraite de Dung (C# /… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 250 | Argumentation Abstraite (Dung) | Python 3 | READY | BETA | 45min | po-2024 | -| 251 | Tweety-5b — Théorie de l'argumentation de Dung… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 252 | Tweety-5d — Synthèse certifiée d'extensions… | Python 3 | READY | BETA | 30min | po-2024 | -| 253 | Tweety-6 — Argumentation structuree (twin C# /… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 254 | Argumentation Structuree | Python 3 | READY | BETA | 30min | po-2024 | -| 255 | Tweety-7a : Frameworks d'Argumentation Etendus… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 256 | Frameworks d'Argumentation Étendus | Python 3 | READY | BETA | 30min | po-2024 | -| 257 | Tweety-7b - Ranking Probabilistic Conditional… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 258 | Sémantiques de Classement et Argumentation… | Python 3 | READY | BETA | 30min | po-2024 | -| 259 | Dialogues Multi-Agents Argumentatifs (twin C#) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 260 | Dialogues Multi-Agents Argumentatifs | Python 3 | READY | BETA | 30min | po-2024 | -| 261 | Préférences et Théorie du Vote en C# / .NET (port… | .NET (C#) | READY | ALPHA | 30min | po-2024 | -| 262 | Préférences et Théorie du Vote | Python 3 | READY | ALPHA | 30min | po-2024 | -| 263 | Tweety .NET - Probe Phase 1 axe 2 : initialisation… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 71 | Lean-31 : les opérateurs de Hecke $T_p$ et $U_p$ —… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 72 | Lean-32 : groupes formels multivariés — compagnon… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 73 | Lean 4 - Quantificateurs et Logique du Premier… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | +| 74 | Lean 5 - Mode Tactique | Lean 4 | READY | BETA | 1h | po-2024 | +| 75 | Lean 6 - Mathlib4 : La Bibliotheque Mathematique | Lean 4 | READY | BETA | 45min | po-2024 | +| 76 | Lean 7 - Integration des LLMs pour l'Assistance… | Python 3 (WSL) | READY | BETA | 45min | po-2024 | +| 77 | Lean 7b - Exemples Progressifs et Benchmarks | Python 3 (WSL) | READY | BETA | 30min | po-2024 | +| 78 | Lean 8 - Agents Autonomes pour Demonstration de… | Python 3 | READY | BETA | 30min | po-2024 | +| 79 | Lean 9 : Multi-Agents avec Semantic Kernel | Python 3 | READY | BETA | 45min | po-2024 | +| 80 | Configuration de l'environnement C# | .NET (C#) | READY | BETA | 45min | po-2024 | +| 81 | Planners-0-Setup | Python 3 | READY | BETA | 30min | po-2024 | +| 82 | Planners-1-Introduction-Csharp : la planification… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 83 | Planners-1-Introduction a la Planification… | Python 3 | READY | BETA | 30min | po-2024 | +| 84 | Planners-2-PDDL-Basics-Csharp | .NET (C#) | READY | BETA | 45min | po-2024 | +| 85 | Planners-2-PDDL-Basics | Python 3 | READY | BETA | 30min | po-2024 | +| 86 | Planners-3 : Recherche dans l'Espace d'Etats —… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 87 | Planners-3-State-Space - Recherche dans l'Espace… | Python 3 | READY | BETA | 45min | po-2024 | +| 88 | Planners-4-Fast-Downward (C#) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 89 | Planners-4-Fast-Downward - Planificateur Classique | Python 3 | READY | BETA | 45min | po-2024 | +| 90 | Planners-5-Heuristics-Csharp | .NET (C#) | READY | BETA | 45min | po-2024 | +| 91 | Planners-5-Heuristiques en Planification | Python 3 | READY | BETA | 45min | po-2024 | +| 92 | Planners-5b — Admissibilité de la relaxation… | Lean 4 (WSL) | READY | BETA | 15min | po-2024 | +| 93 | Planners-5c — Le différentiel d'atteignabilité :… | Python 3 | READY | BETA | 30min | po-2024 | +| 94 | Planners-6-Domains-Csharp — Jumeau C# :… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 95 | Planners-6-Domains - Domaines Classiques de… | Python 3 | READY | BETA | 45min | po-2024 | +| 96 | Planners-7-OR-Tools-Csharp — Jumeau C# : solveur… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 97 | Planners-7-OR-Tools - Programmation par… | Python 3 | READY | BETA | 45min | po-2024 | +| 98 | Planners-8-Temporal — Planification Temporelle… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 99 | Planners-8-Temporal - Planification Temporelle | Python 3 | READY | BETA | 45min | po-2024 | +| 100 | Planners-9-HTN (C#) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 101 | Planners-9-HTN - Planification Hiérarchique | Python 3 | READY | BETA | 45min | po-2024 | +| 102 | Planners-10: LLMs pour la Planification | Python 3 | READY | BETA | 45min | po-2024 | +| 103 | Planners-10b: Le LLM comme reducteur d'espace de… | Python 3 | READY | BETA | 30min | po-2024 | +| 104 | Planners-11: Unified Planning | Python 3 | READY | BETA | 45min | po-2024 | +| 105 | Planners-12: Learning to Plan avec LOOP | Python 3 | READY | BETA | 45min | po-2024 | +| 106 | Z3 (C# / .NET) — Introduction au solveur SMT | .NET (C#) | READY | BETA | 30min | po-2024 | +| 107 | Z3-Python 01 — Introduction a la resolution de… | Python 3 | READY | BETA | 30min | po-2024 | +| 108 | Z3-Python 01b — Du style declaratif LINQ au… | Python 3 | READY | BETA | 15min | po-2024 | +| 109 | Z3 (C# / .NET) — Sudoku par contraintes | .NET (C#) | READY | BETA | 30min | po-2024 | +| 110 | Z3-Python 02 — Sudoku comme problème de… | Python 3 | READY | BETA | 15min | po-2024 | +| 111 | Z3 (C# / .NET) — Tactiques, théories BitVec et… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 112 | Z3-Python 03 — Tactiques et théories | Python 3 | READY | BETA | 30min | po-2024 | +| 113 | Z3 (C# / .NET) — Théorie des chaînes et… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 114 | Z3-Python 04 — Chaînes de caractères et… | Python 3 | READY | BETA | 30min | po-2024 | +| 115 | Z3 (C# / .NET) — Quantificateurs et preuves par… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 116 | Z3-Python 05 — Quantificateurs et preuves… | Python 3 | READY | BETA | 30min | po-2024 | +| 117 | Z3-Python 06 -- Optimisation avancee (twin C#) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 118 | Z3-Python 06 — Optimisation avancee | Python 3 | READY | BETA | 30min | po-2024 | +| 119 | Z3-Python-08 : Ordonnancement de tâches (Job-Shop… | Python 3 | READY | BETA | 30min | po-2024 | +| 120 | Z3-Python-09 : L'enigme d'Einstein (Zebra puzzle) | Python 3 | READY | BETA | 15min | po-2024 | +| 121 | 10. Cryptarithmes (SEND + MORE = MONEY) | Python 3 | READY | BETA | 15min | po-2024 | +| 122 | 11 - Coloration de Graphe avec Z3 | Python 3 | READY | BETA | 30min | po-2024 | +| 123 | 12. Arithmetique reelle : raisonner sur les… | Python 3 | READY | BETA | 30min | po-2024 | +| 124 | 13. UNSAT cores : expliquer l'insatisfiabilite (le… | Python 3 | READY | BETA | 30min | po-2024 | +| 125 | 14. Bit-vectors : verifier le debordement… | Python 3 | READY | BETA | 30min | po-2024 | +| 126 | 15. Tableaux imbriqués et grilles 2D : carrés… | Python 3 | READY | BETA | 30min | po-2024 | +| 127 | 16. Meal-Planner déclaratif : du modèle Z3 au plan… | Python 3 | READY | BETA | 30min | po-2024 | +| 128 | Z3-Python-16b — Meal-Planner : couche de données… | Python 3 | READY | BETA | 30min | po-2024 | +| 129 | Z3-Python-16c — Meal-Planner : capstone patient… | Python 3 | READY | BETA | 30min | po-2024 | +| 130 | Z3-Python-16d — Convergence à l'échelle :… | Python 3 | READY | BETA | 30min | po-2024 | +| 131 | Z3-Python-16e — Meal-Planner : l'optimisation (du… | Python 3 | READY | BETA | 30min | po-2024 | +| 132 | Z3-Python 17 — Théorie des tableaux : Select,… | Python 3 | READY | BETA | 15min | po-2024 | +| 133 | Z3-Python 18 — Sudoku 4x4 : comparaison des modes… | Python 3 | READY | BETA | 15min | po-2024 | +| 134 | LINQ to Z3 - Résolution de Contraintes Déclarative | .NET (C#) | READY | BETA | 45min | po-2024 | +| 135 | Sudoku : Théorème Explicite vs Modèle Implicite… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 136 | Sudoku 4x4 : comparaison des modes Array et… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 137 | Théorie des Tableaux Z3 — Select, Store et… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 138 | Tableaux Imbriqués et Grilles 2D : API Déclarative… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 139 | Notebook 06 — Meal-Planner declaratif : du modèle… | .NET (C#) | READY | BETA | 1h | po-2024 | +| 140 | 07 — Données réelles & externe : Ciqual × RecipeML… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 141 | 08 — Capstone hiérarchique : du squelette int[][]… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 142 | 09 — Convergence à l'échelle : l'encodage décide… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 143 | 10 — Générer un témoin depuis A & ~B (fork… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 144 | Notebook 11 — Ordonnancement d'atelier (Job Shop… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 145 | Notebook 12 - Coloration de graphe : le graphe de… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 146 | Notebook 13 — Cryptarithmes : l'arithmétique… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 147 | Notebook 14 — De SAT à OPT : optimisation et… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 148 | 15 — Théorie des bit-vectors Z3 : vérifier le… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 149 | 16 — Arithmétique réelle Z3 : raisonner sur les… | .NET (C#) | READY | DRAFT | 30min | po-2024 | +| 150 | 17 — UNSAT cores Z3 : expliquer l'insatisfiabilité… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 151 | Notebook 18 - L'enigme d'Einstein : la logique des… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 152 | Introduction au web sémantique avec RDF.Net | .NET (C#) | READY | BETA | 2h+ | po-2024 | +| 153 | SW-1-Setup | .NET (C#) | READY | BETA | 30min | po-2024 | +| 154 | SW-10-CSharp-RDFStar — Jumeau C# : annoter des… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 155 | SW-10-Python-RDFStar | Python 3 | READY | BETA | 45min | po-2024 | +| 156 | SW-11-CSharp-KnowledgeGraphs | .NET (C#) | READY | BETA | 45min | po-2024 | +| 157 | SW-11-Python-KnowledgeGraphs | Python 3 | READY | BETA | 1h | po-2024 | +| 158 | SW-12-Python-GraphRAG | Python 3 | DEMO | BETA | 45min | po-2024 | +| 159 | SW-13-Reasoners | Python 3 | READY | BETA | 1h | po-2024 | +| 160 | SW-13 (C#) : Raisonneurs RDF/OWL — Inferer des… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 161 | SW-14 — Le coup ontologique comme diff de graphe… | Python 3 | READY | BETA | 15min | po-2024 | +| 162 | SW-15 — Le coup argumentatif : greffer AIF sur le… | Python 3 | READY | BETA | 30min | po-2024 | +| 163 | SW-2-RDFBasics | .NET (C#) | READY | BETA | 45min | po-2024 | +| 164 | SW-2b-Python-RDFBasics | Python 3 | READY | BETA | 45min | po-2024 | +| 165 | SW-3-GraphOperations | .NET (C#) | READY | BETA | 1h | po-2024 | +| 166 | SW-3b-Python-GraphOperations | Python 3 (ipykernel) | READY | BETA | 45min | po-2024 | +| 167 | SW-4-SPARQL | .NET (C#) | READY | BETA | 45min | po-2024 | +| 168 | SW-4b-Python-SPARQL | Python 3 | READY | BETA | 45min | po-2024 | +| 169 | SW-5-LinkedData | .NET (C#) | READY | BETA | 45min | po-2024 | +| 170 | SW-5b-Python-LinkedData | .venv (3.12.3) | DEMO | BETA | 45min | po-2024 | +| 171 | SW-6-RDFS | .NET (C#) | READY | BETA | 45min | po-2024 | +| 172 | SW-6b-Python-RDFS | Python 3 (ipykernel) | READY | BETA | 30min | po-2024 | +| 173 | SW-7-OWL | .NET (C#) | READY | BETA | 45min | po-2024 | +| 174 | SW-7b-Python-OWL | Python 3 | DEMO | BETA | 45min | po-2024 | +| 175 | SW-8-CSharp-SHACL | .NET (C#) | READY | BETA | 45min | po-2024 | +| 176 | SW-8-Python-SHACL | Python 3 | READY | BETA | 45min | po-2024 | +| 177 | SW-9-CSharp-JSONLD -- JSON-LD avec dotNetRDF (twin… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 178 | SW-9-Python-JSONLD | Python 3 | READY | BETA | 1h | po-2024 | +| 179 | SC-0-Cypherpunk-Origins - Les origines Cypherpunk… | Python 3 | READY | BETA | 45min | po-2024 | +| 180 | SC-1-Setup-Foundry - Environnement Smart Contracts | Python 3 | READY | BETA | 15min | po-2024 | +| 181 | SC-2-Setup-Web3py - Python et la Blockchain | Python 3 | READY | BETA | 30min | po-2024 | +| 182 | SC-2b - Bac a sable institutionnel : des acteurs,… | Python 3 | READY | BETA | 45min | po-2024 | +| 183 | SC-3-Solidity-Basics - Fondements de Solidity | .venv | READY | BETA | 45min | po-2024 | +| 184 | SC-4-Functions-State - Fonctions et État | Python 3 | READY | BETA | 45min | po-2024 | +| 185 | SC-5-Inheritance - Heritage et Interfaces | Python 3 | READY | BETA | 30min | po-2024 | +| 186 | SC-6-Errors-Events - Erreurs et Événements | Python 3 | READY | BETA | 30min | po-2024 | +| 187 | SC-10-Account-Abstraction - ERC-4337 v0.9 | Python 3 | READY | BETA | 30min | po-2024 | +| 188 | SC-11-LLM-Assisted - Développement Smart Contracts… | Python 3 | READY | BETA | 45min | po-2024 | +| 189 | SC-7-Token-Standards - Standards de Tokens | Python 3 | READY | BETA | 30min | po-2024 | +| 190 | SC-7b : ERC-20 + Lean — vérification formelle de… | Python3 | READY | BETA | 15min | po-2024 | +| 191 | SC-7c : ERC-20 — compagnon natif Lean (kernel… | Lean 4 (WSL) | READY | ALPHA | 30min | po-2024 | +| 192 | SC-8-DeFi-Primitives - Primitives DeFi | Python 3 | READY | BETA | 30min | po-2024 | +| 193 | SC-9-DAO-Governance - Gouvernance DAO | cours-ia | READY | BETA | 30min | po-2024 | +| 194 | SC-12-Foundry-Testing - Tests avec Foundry | Python 3 | READY | BETA | 45min | po-2024 | +| 195 | SC-13-Fuzz-Invariants - Fuzz Testing | Python 3 | READY | BETA | 30min | po-2024 | +| 196 | SC-14-Formal-Vérification - Vérification Formelle | Python 3 | DEMO | BETA | 30min | po-2024 | +| 197 | SC-15-Zero-Knowledge-Proofs - Preuves a… | Python 3 | READY | BETA | 45min | po-2024 | +| 198 | SC-16-Homomorphic-Encryption - Chiffrement… | Python 3 (SC-16 Concrete, WSL) | READY | BETA | 30min | po-2024 | +| 199 | SC-17-E2E-Verifiable-Voting - Vote Electronique… | Python 3 | READY | BETA | 30min | po-2024 | +| 200 | SC-18-Vyper - Smart Contracts en Python-like | Python 3 | READY | BETA | 30min | po-2024 | +| 201 | SC-19-Ripple-XRP - Protocole Ripple et XRP Ledger | Python 3 (smartcontracts) | READY | BETA | 30min | po-2024 | +| 202 | SC-20-Bitcoin-Scripting - Bitcoin, UTXO et Scripts | .venv | READY | BETA | 30min | po-2024 | +| 203 | SC-21-Move-Sui - Move sur Sui | Python 3 | READY | BETA | 30min | po-2024 | +| 204 | SC-22-Solana-Anchor - Solana avec Anchor | Python 3 | READY | BETA | 30min | po-2024 | +| 205 | SC-23-Cross-Chain - Interoperabilite Cross-Chain | Python 3 | READY | BETA | 30min | po-2024 | +| 206 | SC-24 : Deploiement sur Testnets | Python 3 | READY | BETA | 30min | po-2024 | +| 207 | SC-25 : Deploiement Mainnet (L2) | Python 3 | READY | BETA | 30min | po-2024 | +| 208 | SC-26 : Projet Final - DApp Complete | Python 3 | READY | BETA | 15min | po-2024 | +| 209 | SC-27 : Dette d'irréversibilité — la boucle de… | Python 3 | READY | BETA | 30min | po-2024 | +| 210 | SL-1 - Apprentissage Logique : CBH Search et… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 211 | SL-1 - Apprentissage Logique : CBH Search et… | Python 3 | READY | BETA | 45min | po-2024 | +| 212 | SL-10 --- Apprentissage Actif d'Automates (L*… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 213 | SL-10 --- Apprentissage Actif d'Automates (L*… | Python 3 | READY | BETA | 45min | po-2024 | +| 214 | SL-11 --- Capstone : un pipeline neuro-symbolique… | Python 3 | READY | BETA | 45min | po-2024 | +| 215 | SL-12 : Differentiable Logic Gate Networks | Python (difflogic-sl12) | READY | BETA | 45min | po-2024 | +| 216 | SL-12b : Synthèse logique spectrale — Fourier… | Python 3 | READY | BETA | 45min | po-2024 | +| 217 | SL-1b — Apprentissage PAC formellement : le lake… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 218 | SL-2 - Apprentissage et Connaissance : EBL & RBL… | .NET (C#) | READY | ALPHA | 45min | po-2024 | +| 219 | SL-2 --- Apprentissage et Connaissance (EBL & RBL) | Python 3 | READY | BETA | 45min | po-2024 | +| 220 | SL-3 — Apprentissage basé sur la pertinence (twin… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 221 | SL-3 --- Apprentissage Base sur la Pertinence (RBL… | Python 3 | READY | BETA | 45min | po-2024 | +| 222 | SL-4 — Programmation Logique Inductive (ILP) —… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 223 | SL-4 --- Programmation Logique Inductive (ILP) | Python 3 (WSL) | READY | BETA | 45min | po-2024 | +| 224 | SL-5 - Resolution Inverse & ILP (C#) | .NET (C#) | READY | ALPHA | 45min | po-2024 | +| 225 | SL-5 --- Resolution Inverse et Progol (ILP… | Python 3 | READY | BETA | 30min | po-2024 | +| 226 | SL-6 (C#) : Moteurs ILP modernes — apprendre des… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 227 | SL-6 --- Moteurs ILP modernes : Aleph, Metagol,… | Python 3 (WSL) | READY | BETA | 30min | po-2024 | +| 228 | SL-7 : Integration Neuro-Symbolique | Python 3 | READY | BETA | 45min | po-2024 | +| 229 | SL-8 (C#) : ILP Moderne et Knowledge Graphs | .NET (C#) | READY | BETA | 45min | po-2024 | +| 230 | SL-8 - ILP Moderne et Knowledge Graphs | Python 3 | READY | BETA | 45min | po-2024 | +| 231 | SL-9 - LLMs et Apprentissage Symbolique :… | Python 3 | READY | BETA | 45min | po-2024 | +| 232 | Configuration et Installation TweetyProject | Python 3 | READY | BETA | 45min | po-2024 | +| 233 | Tweety-10 — Markov Logic Networks (MLN) en .NET… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 234 | Tweety-10 — Markov Logic Networks (MLN) | Python 3 | READY | BETA | 30min | po-2024 | +| 235 | Tweety-11 — Inférence causale & do-calculus (twin… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 236 | Tweety-11 — Raisonnement Causal : du do-calculus… | Python 3 | READY | BETA | 30min | po-2024 | +| 237 | Argumentation Abstraite : Grounded Extension -… | Python 3 | READY | BETA | 30min | po-2024 | +| 238 | Tweety C# / IKVM - Logiques de Base (Port .NET du… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 239 | Logiques de Base - Propositionnelle et Premier… | Python 3 | READY | BETA | 45min | po-2024 | +| 240 | Tweety C# / IKVM - Sémantique propositionnelle :… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 241 | Tweety-2c — Logique du premier ordre en C#/.NET… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 242 | Tweety-3 — Description Logics en C#/.NET (port… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 243 | Logiques Avancees - DL, Modale, QBF, Conditional | Python 3 | READY | BETA | 45min | po-2024 | +| 244 | Tweety-3 — Conditional Logics en C#/.NET (port… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 245 | Tweety-3 — Argumentation abstraite de Dung en… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 246 | Tweety-3 Modal Logic en C#/.NET (port natif IKVM) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 247 | Tweety-3 - Quantified Boolean Formulas en C#/.NET… | .NET (C#) | READY | BETA | 30min | po-2024 | +| 248 | Tweety-4 — Argumentation structurée ASPIC+ en… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 249 | Tweety C# / IKVM - Revision de Croyances (Port… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 250 | Révision de Croyances et Incohérence | Python 3 | READY | BETA | 30min | po-2024 | +| 251 | Tweety-5 : Argumentation Abstraite de Dung (C# /… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 252 | Argumentation Abstraite (Dung) | Python 3 | READY | BETA | 45min | po-2024 | +| 253 | Tweety-5b — Théorie de l'argumentation de Dung… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 254 | Tweety-5d — Synthèse certifiée d'extensions… | Python 3 | READY | BETA | 30min | po-2024 | +| 255 | Tweety-6 — Argumentation structuree (twin C# /… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 256 | Argumentation Structuree | Python 3 | READY | BETA | 30min | po-2024 | +| 257 | Tweety-7a : Frameworks d'Argumentation Etendus… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 258 | Frameworks d'Argumentation Étendus | Python 3 | READY | BETA | 30min | po-2024 | +| 259 | Tweety-7b - Ranking Probabilistic Conditional… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 260 | Sémantiques de Classement et Argumentation… | Python 3 | READY | BETA | 30min | po-2024 | +| 261 | Dialogues Multi-Agents Argumentatifs (twin C#) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 262 | Dialogues Multi-Agents Argumentatifs | Python 3 | READY | BETA | 30min | po-2024 | +| 263 | Préférences et Théorie du Vote en C# / .NET (port… | .NET (C#) | READY | ALPHA | 30min | po-2024 | +| 264 | Préférences et Théorie du Vote | Python 3 | READY | ALPHA | 30min | po-2024 | +| 265 | Tweety .NET - Probe Phase 1 axe 2 : initialisation… | .NET (C#) | READY | BETA | 30min | po-2024 | ### QuantConnect (110 notebooks) — DEMO:43, READY:67 | ALPHA:12, BETA:61, DRAFT:36, TEMPLATE:1 @@ -787,7 +789,7 @@ Total notebooks: 1125 | 33 | Objectifs d'Apprentissage | Python 3 | READY | DRAFT | 45min | po-2026 | | 34 | QC-Py-27 - Production Deployment | Python 3 | DEMO | DRAFT | 45min | po-2026 | | 35 | QC-Py-28 - Market Regime Detection | Python 3 | DEMO | DRAFT | 1h | po-2026 | -| 36 | QC-Py-30 - LSTM Training Multi-Asset (GPU) | Python 3 | READY | BETA | 45min | po-2026 | +| 36 | QC-Py-30 - LSTM Training Multi-Asset (GPU) | Python 3 | READY | BETA | 1h | po-2026 | | 37 | QC-Py-31 - Transformer Encoder Multi-Asset (GPU) | Python 3 | READY | ALPHA | 45min | po-2026 | | 38 | QC-Py-32 - Reinforcement Learning DQN pour le… | Python 3 | READY | BETA | 45min | po-2026 | | 39 | QC-Py-33 - Reinforcement Learning PPO pour le… | Python 3 | DEMO | BETA | 45min | po-2026 | @@ -863,7 +865,7 @@ Total notebooks: 1125 | 109 | Research QuantBook: VIX-TermStructure (Short… | Python 3 | READY | BETA | 45min | po-2026 | | 110 | Top-4 Sharpe > 0.5 Stratégies: OOS Deep-Dive… | Python 3 | READY | BETA | 15min | po-2026 | -### GameTheory (96 notebooks) — DEMO:1, READY:95 | ALPHA:3, BETA:91, DRAFT:2 +### GameTheory (98 notebooks) — DEMO:1, READY:97 | ALPHA:4, BETA:92, DRAFT:2 | # | Notebook | Kernel | Status | Maturity | Duration | Owner | |---|----------|--------|--------|----------|----------|-------| @@ -900,69 +902,71 @@ Total notebooks: 1125 | 31 | GameTheory-6c (C#) : Jeux Répétés et Théorème Folk | .NET (C#) | READY | BETA | 45min | po-2024 | | 32 | GameTheory-6c : Jeux Répétés et Théorème Folk… | Python 3 | READY | BETA | 30min | po-2024 | | 33 | GameTheory-06d : Sympathie contre Engagement — la… | Python 3 | READY | BETA | 30min | po-2024 | -| 34 | GameTheory-07-ExtensiveForm (Twin C#) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 35 | GameTheory-07-ExtensiveForm | Python 3 | READY | BETA | 45min | po-2024 | -| 36 | GameTheory-08-CombinatorialGames (C#) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 37 | GameTheory 8 - Jeux Combinatoires | Python 3 | READY | BETA | 30min | po-2024 | -| 38 | GameTheory 8b - Jeux Combinatoires en Lean | Lean 4 (WSL) | READY | BETA | 15min | po-2024 | -| 39 | GameTheory 8c - Jeux Combinatoires :… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 40 | GameTheory 8c - Jeux Combinatoires :… | Python 3 | READY | BETA | 30min | po-2024 | -| 41 | GameTheory 8d - Combinatorial Games natif : le… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 42 | GameTheory-09-BackwardInduction (C#) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 43 | GameTheory-09-BackwardInduction | Python 3 | READY | BETA | 45min | po-2024 | -| 44 | Stackelberg : la performativité sans mystère | Python 3 | READY | BETA | 30min | po-2024 | -| 45 | GameTheory-09c : Stackelberg Security Game —… | Python 3 | READY | BETA | 15min | po-2024 | -| 46 | GameTheory-10 — Équilibres Parfaits de Sous-Jeux… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 47 | GameTheory-10-ForwardInduction-SPE | Python 3 | READY | BETA | 45min | po-2024 | -| 48 | GameTheory-11-BayesianGames-Csharp | .NET (C#) | READY | BETA | 45min | po-2024 | -| 49 | GameTheory-11-BayesianGames | Python 3 | READY | BETA | 45min | po-2024 | -| 50 | GameTheory-11b — Jeux Bayésiens en Lean 4… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | -| 51 | GameTheory-12 — Jeux de Réputation (twin C# du… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 52 | GameTheory-12-ReputationGames | Python 3 | READY | BETA | 30min | po-2024 | -| 53 | GameTheory-13 : Jeux a Information Imparfaite et… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 54 | GameTheory-13 : Jeux a Information Imparfaite et… | Python (GameTheory WSL +… | READY | BETA | 1h | po-2024 | -| 55 | GameTheory-13b : Safe Subgame Solving -- quand le… | Python (coursia-ml-training) | READY | BETA | 30min | po-2024 | -| 56 | GameTheory-13c : Safe Subgame Solving en C# — le… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 57 | GameTheory-13d : Optimistic Counterfactual Regret… | Python 3 | READY | BETA | 15min | po-2024 | -| 58 | GameTheory-14 : Jeux Differentiels et Equilibres… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 59 | GameTheory-14 : Jeux Differentiels et Equilibres… | Python 3 | READY | BETA | 45min | po-2024 | -| 60 | GameTheory-15 — Jeux Coopératifs (Twin C#) | .NET (C#) | READY | BETA | 1h | po-2024 | -| 61 | GameTheory-15-CooperativeGames | Python 3 (ipykernel) | READY | BETA | 45min | po-2024 | -| 62 | GameTheory 15b - Jeux Cooperatifs en Lean :… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | -| 63 | GameTheory 15c - Jeux Cooperatifs (C# / .NET) | .NET (C#) | READY | BETA | 45min | po-2024 | -| 64 | GameTheory 15c - Jeux Cooperatifs Lean (Python) | Python (coursia-ml-training) | READY | BETA | 45min | po-2024 | -| 65 | GameTheory 15d - La decomposition de Mobius sur le… | Python 3 | READY | BETA | 30min | po-2024 | -| 66 | GameTheory-15e — Pouvoir coalitionnel : calcul,… | Python 3 | READY | BETA | 30min | po-2024 | -| 67 | GameTheory-16-MechanismDesign (C#) | .NET (C#) | READY | BETA | 30min | po-2024 | -| 68 | GameTheory-16 : Théorie des Mécanismes et Principe… | Python 3 | READY | BETA | 45min | po-2024 | -| 69 | GameTheory-16b : Automated Mechanism Design (AMD) | Python 3 | READY | BETA | 15min | po-2024 | -| 70 | GameTheory-16c : La dimension paiement que le… | Python 3 | READY | BETA | 15min | po-2024 | -| 71 | GameTheory-16d — L'echange de reins : de la valeur… | Python 3 | READY | BETA | 30min | po-2024 | -| 72 | GameTheory-17 (C#) : Multi-Agent Reinforcement… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 73 | GameTheory-17 : Apprentissage par Renforcement… | Python (GameTheory WSL +… | READY | BETA | 30min | po-2024 | -| 74 | Information asymétrique : types privés,… | Python 3 | READY | BETA | 30min | po-2024 | -| 75 | Le marché des lemons : le certificat formel… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 76 | Du marché au bilan : le pont théorie des jeux… | Python 3 | READY | BETA | 30min | po-2024 | -| 77 | Screening, signal et anticipation : les trois… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 78 | GameTheory-18 : Open Games et Lentilles -- la… | Python 3 (ipykernel) | READY | BETA | 30min | po-2024 | -| 79 | GameTheory-18b : Casser la composition — où la… | Python 3 | READY | BETA | 30min | po-2024 | -| 80 | GameTheory-19 : L'abstraction a dette mesurable | Python 3 | READY | BETA | 15min | po-2024 | -| 81 | GameTheory 24 : Le chemin minimal, témoin… | Python 3 | READY | DRAFT | 45min | po-2024 | -| 82 | GameTheory 24b : Le temoin d'impossibilite | Python 3 | READY | BETA | 30min | po-2024 | -| 83 | GameTheory-25 — Loi II, seconde jambe :… | Python 3 | READY | BETA | 30min | po-2024 | -| 84 | GameTheory-26 — Ensembles limites :… | Python 3 | READY | BETA | 30min | po-2024 | -| 85 | GameTheory-27 — L'algorithme de Kuhn-Munkres :… | Python 3 | READY | BETA | 30min | po-2024 | -| 86 | GameTheory 27b — Le lake assignment_lean par son… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | -| 87 | GameTheory-28 : Banc de calibration — humour,… | Python (CoursIA-2 venv) | READY | BETA | 30min | po-2024 | -| 88 | GameTheory-28b : Banc humour — passer à l'échelle | Python 3 | READY | BETA | 30min | po-2024 | -| 89 | SocialChoice 01 : Théorème d'impossibilité d'Arrow… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 90 | SocialChoice 01 - Theoreme d'Arrow : Preuve… | Python 3 | READY | BETA | 30min | po-2024 | -| 91 | SocialChoice 01b - Choix Social Formel en Lean 4 | Lean 4 (WSL) | READY | ALPHA | 45min | po-2024 | -| 92 | SocialChoice 03 : Méthodes de Vote et Paradoxes… | .NET (C#) | READY | ALPHA | 45min | po-2024 | -| 93 | SocialChoice 03 - Méthodes de Vote et Paradoxes | Python 3 | READY | BETA | 45min | po-2024 | -| 94 | SocialChoice 04 : Agregation Computationnelle -… | .NET (C#) | READY | BETA | 45min | po-2024 | -| 95 | SocialChoice 04 - Agregation Computationnelle :… | Python 3 (WSL) | READY | BETA | 45min | po-2024 | -| 96 | SocialChoice-05 : Gibbard-Satterthwaite sans… | Python 3 | READY | BETA | 15min | po-2024 | +| 34 | GameTheory-06e : Transparence des programmes et… | Python 3 (ipykernel) | READY | ALPHA | 15min | po-2024 | +| 35 | GameTheory-07-ExtensiveForm (Twin C#) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 36 | GameTheory-07-ExtensiveForm | Python 3 | READY | BETA | 45min | po-2024 | +| 37 | GameTheory-08-CombinatorialGames (C#) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 38 | GameTheory 8 - Jeux Combinatoires | Python 3 | READY | BETA | 30min | po-2024 | +| 39 | GameTheory 8b - Jeux Combinatoires en Lean | Lean 4 (WSL) | READY | BETA | 15min | po-2024 | +| 40 | GameTheory 8c - Jeux Combinatoires :… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 41 | GameTheory 8c - Jeux Combinatoires :… | Python 3 | READY | BETA | 30min | po-2024 | +| 42 | GameTheory 8d - Combinatorial Games natif : le… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 43 | GameTheory-09-BackwardInduction (C#) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 44 | GameTheory-09-BackwardInduction | Python 3 | READY | BETA | 45min | po-2024 | +| 45 | Stackelberg : la performativité sans mystère | Python 3 | READY | BETA | 30min | po-2024 | +| 46 | GameTheory-09c : Stackelberg Security Game —… | Python 3 | READY | BETA | 15min | po-2024 | +| 47 | GameTheory-10 — Équilibres Parfaits de Sous-Jeux… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 48 | GameTheory-10-ForwardInduction-SPE | Python 3 | READY | BETA | 45min | po-2024 | +| 49 | GameTheory-11-BayesianGames-Csharp | .NET (C#) | READY | BETA | 45min | po-2024 | +| 50 | GameTheory-11-BayesianGames | Python 3 | READY | BETA | 45min | po-2024 | +| 51 | GameTheory-11b — Jeux Bayésiens en Lean 4… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | +| 52 | GameTheory-12 — Jeux de Réputation (twin C# du… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 53 | GameTheory-12-ReputationGames | Python 3 | READY | BETA | 30min | po-2024 | +| 54 | GameTheory-13 : Jeux a Information Imparfaite et… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 55 | GameTheory-13 : Jeux a Information Imparfaite et… | Python (GameTheory WSL +… | READY | BETA | 1h | po-2024 | +| 56 | GameTheory-13b : Safe Subgame Solving -- quand le… | Python (coursia-ml-training) | READY | BETA | 30min | po-2024 | +| 57 | GameTheory-13c : Safe Subgame Solving en C# — le… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 58 | GameTheory-13d : Optimistic Counterfactual Regret… | Python 3 | READY | BETA | 15min | po-2024 | +| 59 | GameTheory-14 : Jeux Differentiels et Equilibres… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 60 | GameTheory-14 : Jeux Differentiels et Equilibres… | Python 3 | READY | BETA | 45min | po-2024 | +| 61 | GameTheory-15 — Jeux Coopératifs (Twin C#) | .NET (C#) | READY | BETA | 1h | po-2024 | +| 62 | GameTheory-15-CooperativeGames | Python 3 (ipykernel) | READY | BETA | 45min | po-2024 | +| 63 | GameTheory 15b - Jeux Cooperatifs en Lean :… | Lean 4 (WSL) | READY | BETA | 45min | po-2024 | +| 64 | GameTheory 15c - Jeux Cooperatifs (C# / .NET) | .NET (C#) | READY | BETA | 45min | po-2024 | +| 65 | GameTheory 15c - Jeux Cooperatifs Lean (Python) | Python (coursia-ml-training) | READY | BETA | 45min | po-2024 | +| 66 | GameTheory 15d - La decomposition de Mobius sur le… | Python 3 | READY | BETA | 30min | po-2024 | +| 67 | GameTheory-15e — Pouvoir coalitionnel : calcul,… | Python 3 | READY | BETA | 30min | po-2024 | +| 68 | GameTheory-16-MechanismDesign (C#) | .NET (C#) | READY | BETA | 30min | po-2024 | +| 69 | GameTheory-16 : Théorie des Mécanismes et Principe… | Python 3 | READY | BETA | 45min | po-2024 | +| 70 | GameTheory-16b : Automated Mechanism Design (AMD) | Python 3 | READY | BETA | 15min | po-2024 | +| 71 | GameTheory-16c : La dimension paiement que le… | Python 3 | READY | BETA | 15min | po-2024 | +| 72 | GameTheory-16d — L'echange de reins : de la valeur… | Python 3 | READY | BETA | 30min | po-2024 | +| 73 | GameTheory-16e : Pilote — joueurs LLM hétérogènes… | Python 3 | READY | BETA | 45min | po-2024 | +| 74 | GameTheory-17 (C#) : Multi-Agent Reinforcement… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 75 | GameTheory-17 : Apprentissage par Renforcement… | Python (GameTheory WSL +… | READY | BETA | 30min | po-2024 | +| 76 | Information asymétrique : types privés,… | Python 3 | READY | BETA | 30min | po-2024 | +| 77 | Le marché des lemons : le certificat formel… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 78 | Du marché au bilan : le pont théorie des jeux… | Python 3 | READY | BETA | 30min | po-2024 | +| 79 | Screening, signal et anticipation : les trois… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 80 | GameTheory-18 : Open Games et Lentilles -- la… | Python 3 (ipykernel) | READY | BETA | 30min | po-2024 | +| 81 | GameTheory-18b : Casser la composition — où la… | Python 3 | READY | BETA | 30min | po-2024 | +| 82 | GameTheory-19 : L'abstraction a dette mesurable | Python 3 | READY | BETA | 15min | po-2024 | +| 83 | GameTheory 24 : Le chemin minimal, témoin… | Python 3 | READY | DRAFT | 45min | po-2024 | +| 84 | GameTheory 24b : Le temoin d'impossibilite | Python 3 | READY | BETA | 30min | po-2024 | +| 85 | GameTheory-25 — Loi II, seconde jambe :… | Python 3 | READY | BETA | 30min | po-2024 | +| 86 | GameTheory-26 — Ensembles limites :… | Python 3 | READY | BETA | 30min | po-2024 | +| 87 | GameTheory-27 — L'algorithme de Kuhn-Munkres :… | Python 3 | READY | BETA | 30min | po-2024 | +| 88 | GameTheory 27b — Le lake assignment_lean par son… | Lean 4 (WSL) | READY | BETA | 30min | po-2024 | +| 89 | GameTheory-28 : Banc de calibration — humour,… | Python (CoursIA-2 venv) | READY | BETA | 30min | po-2024 | +| 90 | GameTheory-28b : Banc humour — passer à l'échelle | Python 3 | READY | BETA | 30min | po-2024 | +| 91 | SocialChoice 01 : Théorème d'impossibilité d'Arrow… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 92 | SocialChoice 01 - Theoreme d'Arrow : Preuve… | Python 3 | READY | BETA | 30min | po-2024 | +| 93 | SocialChoice 01b - Choix Social Formel en Lean 4 | Lean 4 (WSL) | READY | ALPHA | 45min | po-2024 | +| 94 | SocialChoice 03 : Méthodes de Vote et Paradoxes… | .NET (C#) | READY | ALPHA | 45min | po-2024 | +| 95 | SocialChoice 03 - Méthodes de Vote et Paradoxes | Python 3 | READY | BETA | 45min | po-2024 | +| 96 | SocialChoice 04 : Agregation Computationnelle -… | .NET (C#) | READY | BETA | 45min | po-2024 | +| 97 | SocialChoice 04 - Agrégation Computationnelle :… | Python 3 (WSL) | READY | BETA | 45min | po-2024 | +| 98 | SocialChoice-05 : Gibbard-Satterthwaite sans… | Python 3 | READY | BETA | 15min | po-2024 | ### Sudoku (38 notebooks) — DEMO:1, READY:37 | BETA:38 @@ -1034,7 +1038,7 @@ Total notebooks: 1125 | 21 | DecPyMC-2-Utility-Money : Utilite de l'Argent et… | Python 3 (ipykernel) | READY | BETA | 45min | po-2023 | | 22 | DecPyMC-3-Multi-Attribute : Utilite… | Python 3 | READY | BETA | 45min | po-2023 | | 23 | DecPyMC-4-Decision-Networks : Reseaux de Decision | Python 3 | READY | BETA | 30min | po-2023 | -| 24 | DecPyMC-5-Valeur de l'Information | Python 3 | READY | BETA | 45min | po-2023 | +| 24 | DecPyMC-5-Valeur de l'Information | Python 3 | READY | BETA | 1h | po-2023 | | 25 | DecPyMC-6-Systèmes Experts et Decisions Robustes | Python 3 | READY | BETA | 45min | po-2023 | | 26 | DecPyMC-7-MDPs, Bandits et POMDPs | Python 3 | READY | BETA | 45min | po-2023 | | 27 | DecPyMC-8 — Crédibilité actuarielle de… | Python 3 (ipykernel) | READY | BETA | 30min | po-2023 | @@ -1124,7 +1128,7 @@ Total notebooks: 1125 | 37 | ICT-22 — LLMSubstrat : le transformer comme… | Python 3 | READY | BETA | 30min | po-2025 | | 38 | ICT-23 — PersonaCatastrophe : la fronce de Thom… | Python 3 | READY | BETA | 15min | po-2025 | | 39 | ICT-24 — WorkspaceIgnition : l'axe Global… | Python 3 | READY | BETA | 30min | po-2025 | -| 40 | ICT-25 — InoculationRL : GRPO à récompense… | Python 3 | READY | BETA | 45min | po-2025 | +| 40 | ICT-25 — InoculationRL : GRPO à récompense… | Python 3 | READY | BETA | 1h | po-2025 | | 41 | ICT-26 — Convention de signalisation (expérience… | Python 3 | READY | BETA | 30min | po-2025 | | 42 | ICT-27 — Invention de symboles (expérience B,… | Python 3 | READY | BETA | 30min | po-2025 | | 43 | ICT-28 — Adoption collective et seuil de… | Python 3 | READY | BETA | 30min | po-2025 | @@ -1158,7 +1162,7 @@ Total notebooks: 1125 | 71 | IIT-4. Le problème de frontière — qui décide où… | Python 3 (PyPhi/IIT) | READY | BETA | 30min | po-2025 | | 72 | IIT-5. Les lentilles de conscience comme bancs de… | unknown | READY | BETA | 15min | po-2025 | -### RL (25 notebooks) — DEMO:3, READY:22 | BETA:24, DRAFT:1 +### RL (26 notebooks) — DEMO:3, READY:23 | BETA:25, DRAFT:1 | # | Notebook | Kernel | Status | Maturity | Duration | Owner | |---|----------|--------|--------|----------|----------|-------| @@ -1171,28 +1175,29 @@ Total notebooks: 1125 | 7 | RL-15 — GRPO (Group Relative Policy Optimization)… | Python 3 | DEMO | DRAFT | 45min | po-2025 | | 8 | Tutoriel Stable Baselines3 - Premiers pas | Python 3 | READY | BETA | 45min | po-2025 | | 9 | Synthese logique d'un controleur CartPole : le… | Python 3 | READY | BETA | 30min | po-2025 | -| 10 | Notebook 2 – Wrappers Gym, Sauvegarde/Chargement,… | Python 3 | DEMO | BETA | 45min | po-2025 | -| 11 | Notebook 3 – Hindsight Experience Replay (HER) :… | Python 3 | READY | BETA | 45min | po-2025 | -| 12 | RL-4 : Bandits Manchots et le Compromis… | Python 3 | READY | BETA | 45min | po-2025 | -| 13 | RL-5 : MDP, Programmation Dynamique et Q-Learning… | Python 3 | READY | BETA | 1h | po-2025 | -| 14 | RL-6 : Deep Q-Network (DQN) et Policy Gradient | Python 3 | READY | BETA | 45min | po-2025 | -| 15 | RL-6b - Actor-Critic : unir valeur et politique | Python 3 | READY | BETA | 30min | po-2025 | -| 16 | PPO (Proximal Policy Optimization) depuis zero | Python 3 | READY | BETA | 30min | po-2025 | -| 17 | SAC (Soft Actor-Critic) depuis zero | Python 3 | READY | BETA | 30min | po-2025 | -| 18 | GRPO (Group Relative Policy Optimization) depuis… | Python 3 | READY | BETA | 45min | po-2025 | -| 19 | RL-7 : Introduction a l'Apprentissage Multi-Agent | Python 3 | READY | BETA | 30min | po-2025 | -| 20 | RL-8 : Model-Based RL — Dyna-Q et planification | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | -| 21 | RL-9 : RL offline — Behavior Cloning et erreur… | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | -| 22 | RL Post-Training — 1 : PPO pour l'alignement d'un… | Python 3 | READY | BETA | 30min | po-2025 | -| 23 | RL Post-Training — 2 : GRPO minimal — alignement… | Python (coursia-ml-training) | READY | BETA | 45min | po-2025 | -| 24 | RL Post-Training — 3 : Reward hacking — anatomie… | Python (coursia-ml-training) | DEMO | BETA | 45min | po-2025 | -| 25 | RL Post-Training — 4 : DPO offline vs RL online —… | Python (coursia-ml-training) | READY | BETA | 45min | po-2025 | +| 10 | Distiller une politique RL en programme Prolog… | Python 3 | READY | BETA | 45min | po-2025 | +| 11 | Notebook 2 – Wrappers Gym, Sauvegarde/Chargement,… | Python 3 | DEMO | BETA | 45min | po-2025 | +| 12 | Notebook 3 – Hindsight Experience Replay (HER) :… | Python 3 | READY | BETA | 45min | po-2025 | +| 13 | RL-4 : Bandits Manchots et le Compromis… | Python 3 | READY | BETA | 45min | po-2025 | +| 14 | RL-5 : MDP, Programmation Dynamique et Q-Learning… | Python 3 | READY | BETA | 1h | po-2025 | +| 15 | RL-6 : Deep Q-Network (DQN) et Policy Gradient | Python 3 | READY | BETA | 45min | po-2025 | +| 16 | RL-6b - Actor-Critic : unir valeur et politique | Python 3 | READY | BETA | 30min | po-2025 | +| 17 | PPO (Proximal Policy Optimization) depuis zero | Python 3 | READY | BETA | 30min | po-2025 | +| 18 | SAC (Soft Actor-Critic) depuis zero | Python 3 | READY | BETA | 30min | po-2025 | +| 19 | GRPO (Group Relative Policy Optimization) depuis… | Python 3 | READY | BETA | 45min | po-2025 | +| 20 | RL-7 : Introduction a l'Apprentissage Multi-Agent | Python 3 | READY | BETA | 30min | po-2025 | +| 21 | RL-8 : Model-Based RL — Dyna-Q et planification | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | +| 22 | RL-9 : RL offline — Behavior Cloning et erreur… | Python 3 (ipykernel) | READY | BETA | 30min | po-2025 | +| 23 | RL Post-Training — 1 : PPO pour l'alignement d'un… | Python 3 | READY | BETA | 30min | po-2025 | +| 24 | RL Post-Training — 2 : GRPO minimal — alignement… | Python (coursia-ml-training) | READY | BETA | 45min | po-2025 | +| 25 | RL Post-Training — 3 : Reward hacking — anatomie… | Python (coursia-ml-training) | DEMO | BETA | 45min | po-2025 | +| 26 | RL Post-Training — 4 : DPO offline vs RL online —… | Python (coursia-ml-training) | READY | BETA | 45min | po-2025 | ## Requirements -- **API**: 176 notebooks +- **API**: 177 notebooks - **GPU**: 126 notebooks - **Cloud**: 114 notebooks -- **WSL**: 76 notebooks -- **Local**: 710 notebooks \ No newline at end of file +- **WSL**: 78 notebooks +- **Local**: 712 notebooks \ No newline at end of file diff --git a/MyIA.AI.Notebooks/GameTheory/README.md b/MyIA.AI.Notebooks/GameTheory/README.md index dd546d6b15..0e870e2a86 100644 --- a/MyIA.AI.Notebooks/GameTheory/README.md +++ b/MyIA.AI.Notebooks/GameTheory/README.md @@ -4,9 +4,9 @@ La théorie des jeux est le langage mathématique de la stratégie. Elle modélise les situations où des agents rationnels prennent des décisions dont le résultat dépend des choix des autres : enchères, négociations commerciales, élections, poker, guerre commerciale, allocation de ressources. Cette dualité entre coopération et compétition est omniprésente en économie, en sciences politiques et en informatique (mécanismes de vote, smart contracts, réseaux). Le prix Nobel d'économie a été décerné à des théoriciens des jeux à sept reprises entre 1994 et 2020 — c'est un domaine vivant et influent. diff --git a/MyIA.AI.Notebooks/README.md b/MyIA.AI.Notebooks/README.md index 3465e80c91..4702974aad 100644 --- a/MyIA.AI.Notebooks/README.md +++ b/MyIA.AI.Notebooks/README.md @@ -10,9 +10,9 @@ Le catalogue rassemble **plusieurs centaines de notebooks pédagogiques** répar *Marqueur auto-régénéré quotidiennement par `.github/workflows/catalog-cron.yml` (file [`COURSE_CATALOG.generated.md`](../COURSE_CATALOG.generated.md) — source de vérité sur les volumes et la maturité). Toute PR qui modifierait ce bloc est signalée par `catalog-drift.yml` (read-only, catalog-pr-hygiene R1).* diff --git a/MyIA.AI.Notebooks/RL/README.md b/MyIA.AI.Notebooks/RL/README.md index a0ef9c9ee1..49914d9d53 100644 --- a/MyIA.AI.Notebooks/RL/README.md +++ b/MyIA.AI.Notebooks/RL/README.md @@ -4,9 +4,9 @@ > **Note éditoriale (counts)** : Le marqueur `CATALOG-STATUS` ci-dessus est autoritatif pour le compte agrégé (17 notebooks canoniques). Pour la **décomposition langagière par kernel** (`metadata.kernelspec.language`), ce README reste autoritatif car la granularité kernel n'est pas dans le marqueur agrégé ; elle est documentée ici par lecture directe des kernelspecs au 10/07/2026 : diff --git a/MyIA.AI.Notebooks/Search/README.md b/MyIA.AI.Notebooks/Search/README.md index 445b74e9d2..bcc722de59 100644 --- a/MyIA.AI.Notebooks/Search/README.md +++ b/MyIA.AI.Notebooks/Search/README.md @@ -4,7 +4,7 @@ series: Search pedagogical_count: 149 breakdown: Applications=56, Part1-Foundations=40, Part4-Metaheuristics=35, Part2-CSP=18 -maturity: BETA=133, ALPHA=10, DRAFT=6 +maturity: BETA=134, ALPHA=10, DRAFT=5 --> [← Notebooks](../README.md) | [↑ ..](../README.md) | [→ SymbolicAI](../SymbolicAI/README.md) diff --git a/MyIA.AI.Notebooks/SymbolicAI/Lean/README.md b/MyIA.AI.Notebooks/SymbolicAI/Lean/README.md index 55f61b1e07..3bcac15457 100644 --- a/MyIA.AI.Notebooks/SymbolicAI/Lean/README.md +++ b/MyIA.AI.Notebooks/SymbolicAI/Lean/README.md @@ -2,9 +2,9 @@ [← SemanticWeb](../SemanticWeb/README.md) | [↑ SymbolicAI](../README.md) | [Planners →](../Planners/README.md) diff --git a/MyIA.AI.Notebooks/SymbolicAI/README.md b/MyIA.AI.Notebooks/SymbolicAI/README.md index 882d6da8a1..6cdeae7716 100644 --- a/MyIA.AI.Notebooks/SymbolicAI/README.md +++ b/MyIA.AI.Notebooks/SymbolicAI/README.md @@ -4,9 +4,9 @@ > **Note sur les comptes.** Le bloc ci-dessus est un marqueur autoritatif : `` est régénéré quotidiennement par la CI (`.github/workflows/catalog-cron.yml`, 03:37 UTC) sur `main` — pour toute vérification courante du nombre de notebooks et de la maturité, **le catalogue fait foi**. La prose pédagogique ci-dessous mentionne des chiffres précis (ex. « 12 notebooks Python », « 8 jumeaux C# ») qui peuvent dériver localement ; la table « Audit Qualité » (§E) au bas de ce fichier et les READMEs de chaque sous-série ([Tweety](Tweety/README.md), [Lean](Lean/README.md), [SemanticWeb](SemanticWeb/README.md), [Planners](Planners/README.md), [SmartContracts](SmartContracts/README.md), [Argument_Analysis](Argument_Analysis/README.md), [SymbolicLearning](SymbolicLearning/README.md)) sont les sources canoniques pour les détails de chaque sous-série. diff --git a/docs/archive/reference/HEALTH_DASHBOARD.md b/docs/archive/reference/HEALTH_DASHBOARD.md index ae441485e8..e591e4f3b3 100644 --- a/docs/archive/reference/HEALTH_DASHBOARD.md +++ b/docs/archive/reference/HEALTH_DASHBOARD.md @@ -4,51 +4,51 @@ > Ce fichier **n'est pas maintenu à la main** : il est dérivé du catalogue (acceptance #4 de #4210). > Pour le régénérer : `python scripts/notebook_tools/generate_health_dashboard.py`. -**1125** notebooks référencés au catalogue. +**1130** notebooks référencés au catalogue. ## État global | Statut | Count | % | |--------|-------|---| -| READY | 947 | 84.2% | -| DEMO | 175 | 15.6% | +| READY | 953 | 84.3% | +| DEMO | 174 | 15.4% | | BROKEN | 2 | 0.2% | ## Exigences d'environnement (badges) | Exigence | Notebooks concernés | |----------|---------------------| -| **local** (exécutable sans GPU/cloud/WSL) | 710 | -| WSL requis | 76 | +| **local** (exécutable sans GPU/cloud/WSL) | 712 | +| WSL requis | 78 | | GPU requis | 126 | | Cloud requis (QC / GenAI Docker) | 114 | -| API key requise | 176 | +| API key requise | 177 | ## Distribution par série | Série | READY | DEMO | BROKEN | Total | % READY | |-------|-------|------|--------|-------|---------| | CaseStudies | 6 | 0 | 0 | 6 | 100% | -| GameTheory | 95 | 1 | 0 | 96 | 99% | +| GameTheory | 97 | 1 | 0 | 98 | 99% | | GenAI | 101 | 111 | 2 | 215 | 47% | | IIT | 71 | 1 | 0 | 72 | 99% | | ML | 74 | 7 | 0 | 81 | 91% | | Probas | 69 | 0 | 0 | 69 | 100% | | QuantConnect | 67 | 43 | 0 | 110 | 61% | -| RL | 22 | 3 | 0 | 25 | 88% | +| RL | 23 | 3 | 0 | 26 | 88% | | Search | 149 | 0 | 0 | 149 | 100% | | Sudoku | 37 | 1 | 0 | 38 | 97% | -| SymbolicAI | 255 | 8 | 0 | 263 | 97% | +| SymbolicAI | 258 | 7 | 0 | 265 | 97% | | cross-series | 1 | 0 | 0 | 1 | 100% | ## Kernels | Kernel | Count | |--------|-------| -| Python 3 | 731 | +| Python 3 | 733 | | .NET (C#) | 259 | -| Lean 4 (WSL) | 39 | -| Python 3 (ipykernel) | 33 | +| Lean 4 (WSL) | 41 | +| Python 3 (ipykernel) | 34 | | Python (coursia-ml-training) | 12 | | Python 3 (WSL) | 7 | | Python 3 (coursia-ml-training) | 7 | diff --git a/docs/curriculum/ia-classique.md b/docs/curriculum/ia-classique.md index ce91f0ef13..c56cdc44ac 100644 --- a/docs/curriculum/ia-classique.md +++ b/docs/curriculum/ia-classique.md @@ -20,9 +20,9 @@ Algorithmes de recherche classique, satisfaction de contraintes (CSP), résoluti | Métrique | Valeur | |----------|--------| -| Notebooks | 171 | +| Notebooks | 172 | | PRODUCTION | 0 | -| BETA | 171 | +| BETA | 172 | | ALPHA | 0 | ## Search/Applications (55 notebooks) @@ -152,31 +152,32 @@ Algorithmes de recherche classique, satisfaction de contraintes (CSP), résoluti | 16 | [CSP-9-Distributed](../../MyIA.AI.Notebooks/Search/Part2-CSP/CSP-9-Distributed-Csharp.ipynb) | BETA | Oui | | 17 | [CSP-9-Distributed : CSP Distribués (DisCSP)](../../MyIA.AI.Notebooks/Search/Part2-CSP/CSP-9-Distributed.ipynb) | BETA | Oui | -## Search/Part4-Metaheuristics (21 notebooks) +## Search/Part4-Metaheuristics (22 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| | 1 | [MGS-1 : Introduction a MetaGeneticSharp et au moteur…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-01-Introduction.ipynb) | BETA | Oui | -| 2 | [MGS-11 : Synergie d'iles complementaires -- exploration…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-11-IslandSynergy.ipynb) | BETA | Oui | -| 3 | [MGS-13 — Visualiser les paysages dé-biaisés : pourquoi…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-13-LandscapeDebias.ipynb) | BETA | Oui | -| 4 | [MGS-14 — Trouver une synergie (et dire quand il n'y en…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-14-IslandSynergyFound.ipynb) | BETA | Oui | -| 5 | [MGS-15 : Analyse de paysage -- la corrélation…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-15-LandscapeAnalysis.ipynb) | BETA | Oui | -| 6 | [MGS-16-AlgorithmSelection : Sélectionner le bon…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-16-AlgorithmSelection.ipynb) | BETA | Oui | -| 7 | [MGS-17 — Contrôle de paramètres (Parameter Control)](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-17-ParameterControl.ipynb) | BETA | Oui | -| 8 | [MGS-18 — Banc CEC consolide : la combinaison des deux…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-18-CecBanc.ipynb) | BETA | Oui | -| 9 | [MGS-19 — Recuit simulé décomposé : l'opérateur de…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-19-MetropolisReinsertion.ipynb) | BETA | Oui | -| 10 | [MGS-20 : Langage de composition pour métaheuristiques](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-20-Langage-de-Composition.ipynb) | BETA | Oui | -| 11 | [MGS-21 : Représentation contre algorithme — la preuve…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-21-Representation-vs-Algorithme.ipynb) | BETA | Oui | -| 12 | [MGS-3 : L'Eukaryote -- sous-populations et chromosomes…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-03-Eukaryote.ipynb) | BETA | Oui | -| 13 | [MGS-4 : Le Modèle Insulaire -- populations structurees…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-04-Islands.ipynb) | BETA | Oui | -| 14 | [MGS-7 : TSP combinatoire -- la grammaire de composition…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-07-TSP.ipynb) | BETA | Oui | -| 15 | [MGS-7d : Michalewicz (steep ridges) + Dixon-Price…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-07d-MichalewiczDixonPrice.ipynb) | BETA | Oui | -| 16 | [MGS-8 : Fitness Landscape Explorer -- voir la surface…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-08-LandscapeExplorer.ipynb) | BETA | Oui | -| 17 | [MGS-9 - Trouver l'Everest : relief reel et bassins…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-09-EverestRelief.ipynb) | BETA | Oui | +| 2 | [MGS-3 : L'Eukaryote -- sous-populations et chromosomes…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-03-Eukaryote.ipynb) | BETA | Oui | +| 3 | [MGS-4 : Le Modèle Insulaire -- populations structurees…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-04-Islands.ipynb) | BETA | Oui | +| 4 | [MGS-7 : TSP combinatoire -- la grammaire de composition…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-07-TSP.ipynb) | BETA | Oui | +| 5 | [MGS-7d : Michalewicz (steep ridges) + Dixon-Price…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-07d-MichalewiczDixonPrice.ipynb) | BETA | Oui | +| 6 | [MGS-8 : Fitness Landscape Explorer -- voir la surface…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-08-LandscapeExplorer.ipynb) | BETA | Oui | +| 7 | [MGS-9 - Trouver l'Everest : relief reel et bassins…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-09-EverestRelief.ipynb) | BETA | Oui | +| 8 | [MGS-11 : Synergie d'iles complementaires -- exploration…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-11-IslandSynergy.ipynb) | BETA | Oui | +| 9 | [MGS-13 — Visualiser les paysages dé-biaisés : pourquoi…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-13-LandscapeDebias.ipynb) | BETA | Oui | +| 10 | [MGS-14 — Trouver une synergie (et dire quand il n'y en…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-14-IslandSynergyFound.ipynb) | BETA | Oui | +| 11 | [MGS-15 : Analyse de paysage -- la corrélation…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-15-LandscapeAnalysis.ipynb) | BETA | Oui | +| 12 | [MGS-16-AlgorithmSelection : Sélectionner le bon…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-16-AlgorithmSelection.ipynb) | BETA | Oui | +| 13 | [MGS-17 — Contrôle de paramètres (Parameter Control)](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-17-ParameterControl.ipynb) | BETA | Oui | +| 14 | [MGS-18 — Banc CEC consolide : la combinaison des deux…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-18-CecBanc.ipynb) | BETA | Oui | +| 15 | [MGS-19 — Recuit simulé décomposé : l'opérateur de…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-19-MetropolisReinsertion.ipynb) | BETA | Oui | +| 16 | [MGS-20 : Langage de composition pour métaheuristiques](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-20-Langage-de-Composition.ipynb) | BETA | Oui | +| 17 | [MGS-21 : Représentation contre algorithme — la preuve…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-21-Representation-vs-Algorithme.ipynb) | BETA | Oui | | 18 | [MGS-22 : MGS contre mealpy — le bench croisé lib-vs-lib…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-vs-mealpy/MGS-22-MGS-vs-Mealpy.ipynb) | BETA | Oui | | 19 | [MGS-23 : DifferentialEvolution MGS contre mealpy —…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-vs-mealpy/MGS-23-DifferentialEvolution-vs-Mealpy.ipynb) | BETA | Oui | | 20 | [MGS-25 : WhaleOptimisation MGS contre mealpy — le WOA…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-vs-mealpy/MGS-25-WhaleOptimisation-vs-Mealpy.ipynb) | BETA | Oui | | 21 | [MGS-29 : GA MGS compose "Default" contre BaseGA mealpy…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-vs-mealpy/MGS-29-GA-vs-Mealpy.ipynb) | BETA | Oui | +| 22 | [MGS-30 : Scatter Search MGS contre son ombre — la…](../../MyIA.AI.Notebooks/Search/Part4-Metaheuristics/MGS-vs-mealpy/MGS-30-ScatterSearch-Decomposition.ipynb) | BETA | Oui | ## Sudoku (38 notebooks) diff --git a/docs/curriculum/ia-symbolique.md b/docs/curriculum/ia-symbolique.md index bd1caa43ba..167896c85f 100644 --- a/docs/curriculum/ia-symbolique.md +++ b/docs/curriculum/ia-symbolique.md @@ -20,9 +20,9 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, | Métrique | Valeur | |----------|--------| -| Notebooks | 259 | +| Notebooks | 261 | | PRODUCTION | 0 | -| BETA | 253 | +| BETA | 255 | | ALPHA | 6 | ## SymbolicAI (1 notebooks) @@ -63,7 +63,7 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, | 26 | [Argument_Analysis — Argumentation basée sur les valeurs…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/Argument_Analysis_Value_Based_AF.ipynb) | BETA | Oui | | 27 | [I2 - Génération de contre-arguments par raisonnement…](../../MyIA.AI.Notebooks/SymbolicAI/Argument_Analysis/groupe-I2-contre-arguments-aspic/I2_Contre_arguments_ASPIC.ipynb) | BETA | Oui | -## SymbolicAI/Lean (47 notebooks) +## SymbolicAI/Lean (49 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -107,13 +107,15 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, | 38 | [Lean-29 : coloration d'arêtes et conjecture de Tutte —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-29-EdgeColoring-Tutte-Companion.ipynb) | BETA | Non | | 39 | [Lean 3 - Propositions et Preuves](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-3-Propositions-Proofs.ipynb) | BETA | Non | | 40 | [Lean-30 : Le problème de Hopf sur S⁶ — digestion d'une…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-30-Complex-Structure-S6.ipynb) | BETA | Non | -| 41 | [Lean 4 - Quantificateurs et Logique du Premier Ordre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-4-Quantifiers.ipynb) | BETA | Non | -| 42 | [Lean 5 - Mode Tactique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-5-Tactics.ipynb) | BETA | Non | -| 43 | [Lean 6 - Mathlib4 : La Bibliotheque Mathematique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-6-Mathlib-Essentials.ipynb) | BETA | Non | -| 44 | [Lean 7 - Integration des LLMs pour l'Assistance aux…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-7-LLM-Integration.ipynb) | BETA | Non | -| 45 | [Lean 7b - Exemples Progressifs et Benchmarks](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-7b-Examples.ipynb) | BETA | Non | -| 46 | [Lean 8 - Agents Autonomes pour Demonstration de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-8-Agentic-Proving.ipynb) | BETA | Non | -| 47 | [Lean 9 : Multi-Agents avec Semantic Kernel](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-9-SK-Multi-Agents.ipynb) | BETA | Non | +| 41 | [Lean-31 : les opérateurs de Hecke $T_p$ et $U_p$ —…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-31-Hecke-Operators-Native.ipynb) | BETA | Non | +| 42 | [Lean-32 : groupes formels multivariés — compagnon natif](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-32-FormalGroups-Native.ipynb) | BETA | Non | +| 43 | [Lean 4 - Quantificateurs et Logique du Premier Ordre](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-4-Quantifiers.ipynb) | BETA | Non | +| 44 | [Lean 5 - Mode Tactique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-5-Tactics.ipynb) | BETA | Non | +| 45 | [Lean 6 - Mathlib4 : La Bibliotheque Mathematique](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-6-Mathlib-Essentials.ipynb) | BETA | Non | +| 46 | [Lean 7 - Integration des LLMs pour l'Assistance aux…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-7-LLM-Integration.ipynb) | BETA | Non | +| 47 | [Lean 7b - Exemples Progressifs et Benchmarks](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-7b-Examples.ipynb) | BETA | Non | +| 48 | [Lean 8 - Agents Autonomes pour Demonstration de…](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-8-Agentic-Proving.ipynb) | BETA | Non | +| 49 | [Lean 9 : Multi-Agents avec Semantic Kernel](../../MyIA.AI.Notebooks/SymbolicAI/Lean/Lean-9-SK-Multi-Agents.ipynb) | BETA | Non | ## SymbolicAI/Planners (25 notebooks) @@ -239,7 +241,7 @@ Preuves formelles en Lean 4, logique probabiliste avec Tweety, web sémantique, | 6 | [SC-4-Functions-State - Fonctions et État](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-4-Functions-State.ipynb) | BETA | Oui | | 7 | [SC-5-Inheritance - Heritage et Interfaces](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-5-Inheritance.ipynb) | BETA | Oui | | 8 | [SC-6-Errors-Events - Erreurs et Événements](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/01-Solidity-Foundation/SC-6-Errors-Events.ipynb) | BETA | Oui | -| 9 | [SC-10-Account-Abstraction - ERC-4337](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-10-Account-Abstraction.ipynb) | BETA | Oui | +| 9 | [SC-10-Account-Abstraction - ERC-4337 v0.9](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-10-Account-Abstraction.ipynb) | BETA | Oui | | 10 | [SC-11-LLM-Assisted - Développement Smart Contracts…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-11-LLM-Assisted.ipynb) | BETA | Non | | 11 | [SC-7-Token-Standards - Standards de Tokens](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-7-Token-Standards.ipynb) | BETA | Oui | | 12 | [SC-7b : ERC-20 + Lean — vérification formelle de…](../../MyIA.AI.Notebooks/SymbolicAI/SmartContracts/02-Solidity-Advanced/SC-7b-ERC20-Lean-Verification-Companion.ipynb) | BETA | Non | diff --git a/docs/curriculum/recherche.md b/docs/curriculum/recherche.md index 74176e4a9b..354561a960 100644 --- a/docs/curriculum/recherche.md +++ b/docs/curriculum/recherche.md @@ -20,12 +20,12 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | Métrique | Valeur | |----------|--------| -| Notebooks | 251 | +| Notebooks | 254 | | PRODUCTION | 0 | -| BETA | 246 | -| ALPHA | 5 | +| BETA | 248 | +| ALPHA | 6 | -## GameTheory (86 notebooks) +## GameTheory (88 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -61,60 +61,62 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | 30 | [GameTheory-6c (C#) : Jeux Répétés et Théorème Folk](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06c-RepeatedGames-FolkTheorem-Csharp.ipynb) | BETA | Oui | | 31 | [GameTheory-6c : Jeux Répétés et Théorème Folk (Folk…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06c-RepeatedGames-FolkTheorem.ipynb) | BETA | Oui | | 32 | [GameTheory-06d : Sympathie contre Engagement — la…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06d-Sympathie-vs-Engagement.ipynb) | BETA | Oui | -| 33 | [GameTheory-07-ExtensiveForm (Twin C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-07-ExtensiveForm-Csharp.ipynb) | BETA | Oui | -| 34 | [GameTheory-07-ExtensiveForm](../../MyIA.AI.Notebooks/GameTheory/GameTheory-07-ExtensiveForm.ipynb) | BETA | Oui | -| 35 | [GameTheory-08-CombinatorialGames (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08-CombinatorialGames-Csharp.ipynb) | BETA | Oui | -| 36 | [GameTheory 8 - Jeux Combinatoires](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08-CombinatorialGames.ipynb) | BETA | Oui | -| 37 | [GameTheory 8b - Jeux Combinatoires en Lean](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08b-Lean-CombinatorialGames.ipynb) | BETA | Non | -| 38 | [GameTheory 8c - Jeux Combinatoires : Approfondissement…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08c-CombinatorialGames-Csharp.ipynb) | BETA | Oui | -| 39 | [GameTheory 8c - Jeux Combinatoires : Approfondissement…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08c-CombinatorialGames-Python.ipynb) | BETA | Oui | -| 40 | [GameTheory 8d - Combinatorial Games natif : le lake…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08d-Lean-CGT-Native.ipynb) | BETA | Non | -| 41 | [GameTheory-09-BackwardInduction (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09-BackwardInduction-Csharp.ipynb) | BETA | Oui | -| 42 | [GameTheory-09-BackwardInduction](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09-BackwardInduction.ipynb) | BETA | Oui | -| 43 | [Stackelberg : la performativité sans mystère](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09b-Commitment-Stackelberg.ipynb) | BETA | Oui | -| 44 | [GameTheory-09c : Stackelberg Security Game —…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09c-Stackelberg-SecurityGame.ipynb) | BETA | Oui | -| 45 | [GameTheory-10 — Équilibres Parfaits de Sous-Jeux et…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-10-ForwardInduction-SPE-Csharp.ipynb) | BETA | Oui | -| 46 | [GameTheory-10-ForwardInduction-SPE](../../MyIA.AI.Notebooks/GameTheory/GameTheory-10-ForwardInduction-SPE.ipynb) | BETA | Oui | -| 47 | [GameTheory-11-BayesianGames-Csharp](../../MyIA.AI.Notebooks/GameTheory/GameTheory-11-BayesianGames-Csharp.ipynb) | BETA | Oui | -| 48 | [GameTheory-11-BayesianGames](../../MyIA.AI.Notebooks/GameTheory/GameTheory-11-BayesianGames.ipynb) | BETA | Oui | -| 49 | [GameTheory-11b — Jeux Bayésiens en Lean 4 (companion)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-11b-Lean-BayesianGamesExt.ipynb) | BETA | Non | -| 50 | [GameTheory-12 — Jeux de Réputation (twin C# du notebook…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-12-ReputationGames-Csharp.ipynb) | BETA | Oui | -| 51 | [GameTheory-12-ReputationGames](../../MyIA.AI.Notebooks/GameTheory/GameTheory-12-ReputationGames.ipynb) | BETA | Oui | -| 52 | [GameTheory-13 : Jeux a Information Imparfaite et CFR…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13-ImperfectInfo-CFR-Csharp.ipynb) | BETA | Oui | -| 53 | [GameTheory-13 : Jeux a Information Imparfaite et CFR](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13-ImperfectInfo-CFR.ipynb) | BETA | Non | -| 54 | [GameTheory-13b : Safe Subgame Solving -- quand le…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13b-Safe-Subgame-Solving.ipynb) | BETA | Oui | -| 55 | [GameTheory-13c : Safe Subgame Solving en C# — le twin…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13c-Safe-Subgame-Solving-Csharp.ipynb) | BETA | Oui | -| 56 | [GameTheory-13d : Optimistic Counterfactual Regret…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13d-Optimistic-CFR.ipynb) | BETA | Oui | -| 57 | [GameTheory-14 : Jeux Differentiels et Equilibres de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-14-DifferentialGames-Csharp.ipynb) | BETA | Oui | -| 58 | [GameTheory-14 : Jeux Differentiels et Equilibres de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-14-DifferentialGames.ipynb) | BETA | Oui | -| 59 | [GameTheory-15 — Jeux Coopératifs (Twin C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15-CooperativeGames-Csharp.ipynb) | BETA | Oui | -| 60 | [GameTheory-15-CooperativeGames](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15-CooperativeGames.ipynb) | BETA | Oui | -| 61 | [GameTheory 15b - Jeux Cooperatifs en Lean :…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15b-Lean-CooperativeGames.ipynb) | BETA | Non | -| 62 | [GameTheory 15c - Jeux Cooperatifs (C# / .NET)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15c-CooperativeGames-Csharp.ipynb) | BETA | Oui | -| 63 | [GameTheory 15c - Jeux Cooperatifs Lean (Python)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15c-CooperativeGames-Python.ipynb) | BETA | Oui | -| 64 | [GameTheory 15d - La decomposition de Mobius sur le…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15d-Mobius-Coalitions.ipynb) | BETA | Oui | -| 65 | [GameTheory-15e — Pouvoir coalitionnel : calcul, SMT…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15e-Coalition-Power-SMT.ipynb) | BETA | Oui | -| 66 | [GameTheory-16-MechanismDesign (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16-MechanismDesign-Csharp.ipynb) | BETA | Oui | -| 67 | [GameTheory-16 : Théorie des Mécanismes et Principe de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16-MechanismDesign.ipynb) | BETA | Oui | -| 68 | [GameTheory-16b : Automated Mechanism Design (AMD)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16b-Automated-Mechanism-Design.ipynb) | BETA | Oui | -| 69 | [GameTheory-16c : La dimension paiement que le designer…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16c-Extraction-de-Revenu-DSIC-IR.ipynb) | BETA | Oui | -| 70 | [GameTheory-16d — L'echange de reins : de la valeur…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16d-Echange-de-Reins.ipynb) | BETA | Oui | -| 71 | [GameTheory-17 (C#) : Multi-Agent Reinforcement Learning…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17-MultiAgent-RL-Csharp.ipynb) | BETA | Oui | -| 72 | [GameTheory-17 : Apprentissage par Renforcement…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17-MultiAgent-RL.ipynb) | BETA | Oui | -| 73 | [Information asymétrique : types privés, antisélection…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17b-Asymmetric-Information.ipynb) | BETA | Oui | -| 74 | [Le marché des lemons : le certificat formel exécuté](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17c-Lean-Lemons-Certificat.ipynb) | BETA | Non | -| 75 | [Du marché au bilan : le pont théorie des jeux théorie…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17c-Market-to-Balance-Sheet.ipynb) | BETA | Oui | -| 76 | [Screening, signal et anticipation : les trois réponses…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17d-Lean-Screening-Signaling.ipynb) | BETA | Non | -| 77 | [GameTheory-18 : Open Games et Lentilles -- la…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18-Open-Games-et-Lentilles.ipynb) | BETA | Oui | -| 78 | [GameTheory-18b : Casser la composition — où la…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18b-Casser-la-Composition.ipynb) | BETA | Oui | -| 79 | [GameTheory-19 : L'abstraction a dette mesurable](../../MyIA.AI.Notebooks/GameTheory/GameTheory-19-Abstraction-a-Dette.ipynb) | BETA | Oui | -| 80 | [GameTheory 24b : Le temoin d'impossibilite](../../MyIA.AI.Notebooks/GameTheory/GameTheory-24b-Chemin-Minimal-Temoins-Impossibilite.ipynb) | BETA | Oui | -| 81 | [GameTheory-25 — Loi II, seconde jambe : synthétiser un…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-25-Loi-II-Translateur-Life.ipynb) | BETA | Oui | -| 82 | [GameTheory-26 — Ensembles limites : Poincaré-Bendixson…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-26-Ensembles-Limites-Poincare-Bendixson.ipynb) | BETA | Oui | -| 83 | [GameTheory-27 — L'algorithme de Kuhn-Munkres :…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-27-Munkres-Assignment.ipynb) | BETA | Oui | -| 84 | [GameTheory 27b — Le lake assignment_lean par son…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-27b-Lean-Assignment-Native.ipynb) | BETA | Non | -| 85 | [GameTheory-28 : Banc de calibration — humour, forme…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-28-Humour-Banc.ipynb) | BETA | Oui | -| 86 | [GameTheory-28b : Banc humour — passer à l'échelle](../../MyIA.AI.Notebooks/GameTheory/GameTheory-28b-Humour-Banc-Dur.ipynb) | BETA | Non | +| 33 | [GameTheory-06e : Transparence des programmes et issue…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-06e-Open-Source-Game-Theory.ipynb) | ALPHA | Oui | +| 34 | [GameTheory-07-ExtensiveForm (Twin C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-07-ExtensiveForm-Csharp.ipynb) | BETA | Oui | +| 35 | [GameTheory-07-ExtensiveForm](../../MyIA.AI.Notebooks/GameTheory/GameTheory-07-ExtensiveForm.ipynb) | BETA | Oui | +| 36 | [GameTheory-08-CombinatorialGames (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08-CombinatorialGames-Csharp.ipynb) | BETA | Oui | +| 37 | [GameTheory 8 - Jeux Combinatoires](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08-CombinatorialGames.ipynb) | BETA | Oui | +| 38 | [GameTheory 8b - Jeux Combinatoires en Lean](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08b-Lean-CombinatorialGames.ipynb) | BETA | Non | +| 39 | [GameTheory 8c - Jeux Combinatoires : Approfondissement…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08c-CombinatorialGames-Csharp.ipynb) | BETA | Oui | +| 40 | [GameTheory 8c - Jeux Combinatoires : Approfondissement…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08c-CombinatorialGames-Python.ipynb) | BETA | Oui | +| 41 | [GameTheory 8d - Combinatorial Games natif : le lake…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-08d-Lean-CGT-Native.ipynb) | BETA | Non | +| 42 | [GameTheory-09-BackwardInduction (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09-BackwardInduction-Csharp.ipynb) | BETA | Oui | +| 43 | [GameTheory-09-BackwardInduction](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09-BackwardInduction.ipynb) | BETA | Oui | +| 44 | [Stackelberg : la performativité sans mystère](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09b-Commitment-Stackelberg.ipynb) | BETA | Oui | +| 45 | [GameTheory-09c : Stackelberg Security Game —…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-09c-Stackelberg-SecurityGame.ipynb) | BETA | Oui | +| 46 | [GameTheory-10 — Équilibres Parfaits de Sous-Jeux et…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-10-ForwardInduction-SPE-Csharp.ipynb) | BETA | Oui | +| 47 | [GameTheory-10-ForwardInduction-SPE](../../MyIA.AI.Notebooks/GameTheory/GameTheory-10-ForwardInduction-SPE.ipynb) | BETA | Oui | +| 48 | [GameTheory-11-BayesianGames-Csharp](../../MyIA.AI.Notebooks/GameTheory/GameTheory-11-BayesianGames-Csharp.ipynb) | BETA | Oui | +| 49 | [GameTheory-11-BayesianGames](../../MyIA.AI.Notebooks/GameTheory/GameTheory-11-BayesianGames.ipynb) | BETA | Oui | +| 50 | [GameTheory-11b — Jeux Bayésiens en Lean 4 (companion)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-11b-Lean-BayesianGamesExt.ipynb) | BETA | Non | +| 51 | [GameTheory-12 — Jeux de Réputation (twin C# du notebook…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-12-ReputationGames-Csharp.ipynb) | BETA | Oui | +| 52 | [GameTheory-12-ReputationGames](../../MyIA.AI.Notebooks/GameTheory/GameTheory-12-ReputationGames.ipynb) | BETA | Oui | +| 53 | [GameTheory-13 : Jeux a Information Imparfaite et CFR…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13-ImperfectInfo-CFR-Csharp.ipynb) | BETA | Oui | +| 54 | [GameTheory-13 : Jeux a Information Imparfaite et CFR](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13-ImperfectInfo-CFR.ipynb) | BETA | Non | +| 55 | [GameTheory-13b : Safe Subgame Solving -- quand le…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13b-Safe-Subgame-Solving.ipynb) | BETA | Oui | +| 56 | [GameTheory-13c : Safe Subgame Solving en C# — le twin…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13c-Safe-Subgame-Solving-Csharp.ipynb) | BETA | Oui | +| 57 | [GameTheory-13d : Optimistic Counterfactual Regret…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-13d-Optimistic-CFR.ipynb) | BETA | Oui | +| 58 | [GameTheory-14 : Jeux Differentiels et Equilibres de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-14-DifferentialGames-Csharp.ipynb) | BETA | Oui | +| 59 | [GameTheory-14 : Jeux Differentiels et Equilibres de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-14-DifferentialGames.ipynb) | BETA | Oui | +| 60 | [GameTheory-15 — Jeux Coopératifs (Twin C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15-CooperativeGames-Csharp.ipynb) | BETA | Oui | +| 61 | [GameTheory-15-CooperativeGames](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15-CooperativeGames.ipynb) | BETA | Oui | +| 62 | [GameTheory 15b - Jeux Cooperatifs en Lean :…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15b-Lean-CooperativeGames.ipynb) | BETA | Non | +| 63 | [GameTheory 15c - Jeux Cooperatifs (C# / .NET)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15c-CooperativeGames-Csharp.ipynb) | BETA | Oui | +| 64 | [GameTheory 15c - Jeux Cooperatifs Lean (Python)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15c-CooperativeGames-Python.ipynb) | BETA | Oui | +| 65 | [GameTheory 15d - La decomposition de Mobius sur le…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15d-Mobius-Coalitions.ipynb) | BETA | Oui | +| 66 | [GameTheory-15e — Pouvoir coalitionnel : calcul, SMT…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-15e-Coalition-Power-SMT.ipynb) | BETA | Oui | +| 67 | [GameTheory-16-MechanismDesign (C#)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16-MechanismDesign-Csharp.ipynb) | BETA | Oui | +| 68 | [GameTheory-16 : Théorie des Mécanismes et Principe de…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16-MechanismDesign.ipynb) | BETA | Oui | +| 69 | [GameTheory-16b : Automated Mechanism Design (AMD)](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16b-Automated-Mechanism-Design.ipynb) | BETA | Oui | +| 70 | [GameTheory-16c : La dimension paiement que le designer…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16c-Extraction-de-Revenu-DSIC-IR.ipynb) | BETA | Oui | +| 71 | [GameTheory-16d — L'echange de reins : de la valeur…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16d-Echange-de-Reins.ipynb) | BETA | Oui | +| 72 | [GameTheory-16e : Pilote — joueurs LLM hétérogènes sur…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-16e-LLM-Players-Othman-Sandholm.ipynb) | BETA | Non | +| 73 | [GameTheory-17 (C#) : Multi-Agent Reinforcement Learning…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17-MultiAgent-RL-Csharp.ipynb) | BETA | Oui | +| 74 | [GameTheory-17 : Apprentissage par Renforcement…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17-MultiAgent-RL.ipynb) | BETA | Oui | +| 75 | [Information asymétrique : types privés, antisélection…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17b-Asymmetric-Information.ipynb) | BETA | Oui | +| 76 | [Le marché des lemons : le certificat formel exécuté](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17c-Lean-Lemons-Certificat.ipynb) | BETA | Non | +| 77 | [Du marché au bilan : le pont théorie des jeux théorie…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17c-Market-to-Balance-Sheet.ipynb) | BETA | Oui | +| 78 | [Screening, signal et anticipation : les trois réponses…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-17d-Lean-Screening-Signaling.ipynb) | BETA | Non | +| 79 | [GameTheory-18 : Open Games et Lentilles -- la…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18-Open-Games-et-Lentilles.ipynb) | BETA | Oui | +| 80 | [GameTheory-18b : Casser la composition — où la…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-18b-Casser-la-Composition.ipynb) | BETA | Oui | +| 81 | [GameTheory-19 : L'abstraction a dette mesurable](../../MyIA.AI.Notebooks/GameTheory/GameTheory-19-Abstraction-a-Dette.ipynb) | BETA | Oui | +| 82 | [GameTheory 24b : Le temoin d'impossibilite](../../MyIA.AI.Notebooks/GameTheory/GameTheory-24b-Chemin-Minimal-Temoins-Impossibilite.ipynb) | BETA | Oui | +| 83 | [GameTheory-25 — Loi II, seconde jambe : synthétiser un…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-25-Loi-II-Translateur-Life.ipynb) | BETA | Oui | +| 84 | [GameTheory-26 — Ensembles limites : Poincaré-Bendixson…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-26-Ensembles-Limites-Poincare-Bendixson.ipynb) | BETA | Oui | +| 85 | [GameTheory-27 — L'algorithme de Kuhn-Munkres :…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-27-Munkres-Assignment.ipynb) | BETA | Oui | +| 86 | [GameTheory 27b — Le lake assignment_lean par son…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-27b-Lean-Assignment-Native.ipynb) | BETA | Non | +| 87 | [GameTheory-28 : Banc de calibration — humour, forme…](../../MyIA.AI.Notebooks/GameTheory/GameTheory-28-Humour-Banc.ipynb) | BETA | Oui | +| 88 | [GameTheory-28b : Banc humour — passer à l'échelle](../../MyIA.AI.Notebooks/GameTheory/GameTheory-28b-Humour-Banc-Dur.ipynb) | BETA | Non | ## GameTheory/SocialChoice (8 notebooks) @@ -126,7 +128,7 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | 4 | [SocialChoice 03 : Méthodes de Vote et Paradoxes (twin…](../../MyIA.AI.Notebooks/GameTheory/SocialChoice/03-Voting-Methods-Csharp.ipynb) | ALPHA | Oui | | 5 | [SocialChoice 03 - Méthodes de Vote et Paradoxes](../../MyIA.AI.Notebooks/GameTheory/SocialChoice/03-Voting-Methods.ipynb) | BETA | Oui | | 6 | [SocialChoice 04 : Agregation Computationnelle - SAT et…](../../MyIA.AI.Notebooks/GameTheory/SocialChoice/04-Computational-Aggregation-SAT-Z3-Csharp.ipynb) | BETA | Oui | -| 7 | [SocialChoice 04 - Agregation Computationnelle : SAT et…](../../MyIA.AI.Notebooks/GameTheory/SocialChoice/04-Computational-Aggregation-SAT-Z3.ipynb) | BETA | Oui | +| 7 | [SocialChoice 04 - Agrégation Computationnelle : SAT et…](../../MyIA.AI.Notebooks/GameTheory/SocialChoice/04-Computational-Aggregation-SAT-Z3.ipynb) | BETA | Oui | | 8 | [SocialChoice-05 : Gibbard-Satterthwaite sans mystere -…](../../MyIA.AI.Notebooks/GameTheory/SocialChoice/05-Gibbard-Satterthwaite.ipynb) | BETA | Oui | ## IIT (5 notebooks) @@ -297,7 +299,7 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | 18 | [18. Detection de Rupture (Change-Point) : inferer le…](../../MyIA.AI.Notebooks/Probas/PyMC/PyMC-18-Change-Point.ipynb) | BETA | Oui | | 19 | [19. Analyse de survie / fiabilite bayesienne : inferer…](../../MyIA.AI.Notebooks/Probas/PyMC/PyMC-19-Survival-Analysis.ipynb) | BETA | Oui | -## RL (24 notebooks) +## RL (25 notebooks) | # | Notebook | Maturité | Exécutable | |---|----------|----------|------------| @@ -309,19 +311,20 @@ Inférence probabiliste (Infer.NET, Pyro, PyMC), théorie de l'information inté | 6 | [Hierarchical RL — l'Option framework de Sutton, Precup…](../../MyIA.AI.Notebooks/RL/rl_14_hierarchical_rl.ipynb) | BETA | Oui | | 7 | [Tutoriel Stable Baselines3 - Premiers pas](../../MyIA.AI.Notebooks/RL/rl_1_intro_cartpole.ipynb) | BETA | Oui | | 8 | [Synthese logique d'un controleur CartPole : le bitwise…](../../MyIA.AI.Notebooks/RL/rl_1b_bitwise_logic_synthesis.ipynb) | BETA | Oui | -| 9 | [Notebook 2 – Wrappers Gym, Sauvegarde/Chargement,…](../../MyIA.AI.Notebooks/RL/rl_2_wrappers_sauvegarde_callbacks.ipynb) | BETA | Non | -| 10 | [Notebook 3 – Hindsight Experience Replay (HER) : du…](../../MyIA.AI.Notebooks/RL/rl_3_experience_replay_her.ipynb) | BETA | Oui | -| 11 | [RL-4 : Bandits Manchots et le Compromis…](../../MyIA.AI.Notebooks/RL/rl_4_multi_armed_bandits.ipynb) | BETA | Oui | -| 12 | [RL-5 : MDP, Programmation Dynamique et Q-Learning…](../../MyIA.AI.Notebooks/RL/rl_5_mdp_dp_qlearning.ipynb) | BETA | Oui | -| 13 | [RL-6 : Deep Q-Network (DQN) et Policy Gradient](../../MyIA.AI.Notebooks/RL/rl_6_dqn_policy_gradient.ipynb) | BETA | Oui | -| 14 | [RL-6b - Actor-Critic : unir valeur et politique](../../MyIA.AI.Notebooks/RL/rl_6b_actor_critic.ipynb) | BETA | Oui | -| 15 | [PPO (Proximal Policy Optimization) depuis zero](../../MyIA.AI.Notebooks/RL/rl_6c_ppo_from_scratch.ipynb) | BETA | Oui | -| 16 | [SAC (Soft Actor-Critic) depuis zero](../../MyIA.AI.Notebooks/RL/rl_6d_sac_from_scratch.ipynb) | BETA | Oui | -| 17 | [GRPO (Group Relative Policy Optimization) depuis zero](../../MyIA.AI.Notebooks/RL/rl_6e_grpo_from_scratch.ipynb) | BETA | Non | -| 18 | [RL-7 : Introduction a l'Apprentissage Multi-Agent](../../MyIA.AI.Notebooks/RL/rl_7_multi_agent_rl.ipynb) | BETA | Oui | -| 19 | [RL-8 : Model-Based RL — Dyna-Q et planification](../../MyIA.AI.Notebooks/RL/rl_8_model_based_dyna_q.ipynb) | BETA | Oui | -| 20 | [RL-9 : RL offline — Behavior Cloning et erreur…](../../MyIA.AI.Notebooks/RL/rl_9_offline_rl.ipynb) | BETA | Oui | -| 21 | [RL Post-Training — 1 : PPO pour l'alignement d'un petit…](../../MyIA.AI.Notebooks/RL/rlpt_1_ppo_lm_rlhf.ipynb) | BETA | Oui | -| 22 | [RL Post-Training — 2 : GRPO minimal — alignement d'un…](../../MyIA.AI.Notebooks/RL/rlpt_2_grpo_minimal.ipynb) | BETA | Non | -| 23 | [RL Post-Training — 3 : Reward hacking — anatomie d'un…](../../MyIA.AI.Notebooks/RL/rlpt_3_reward_hacking.ipynb) | BETA | Non | -| 24 | [RL Post-Training — 4 : DPO offline vs RL online — même…](../../MyIA.AI.Notebooks/RL/rlpt_4_dpo_vs_ppo.ipynb) | BETA | Non | +| 9 | [Distiller une politique RL en programme Prolog…](../../MyIA.AI.Notebooks/RL/rl_1c_prolog_distillation.ipynb) | BETA | Oui | +| 10 | [Notebook 2 – Wrappers Gym, Sauvegarde/Chargement,…](../../MyIA.AI.Notebooks/RL/rl_2_wrappers_sauvegarde_callbacks.ipynb) | BETA | Non | +| 11 | [Notebook 3 – Hindsight Experience Replay (HER) : du…](../../MyIA.AI.Notebooks/RL/rl_3_experience_replay_her.ipynb) | BETA | Oui | +| 12 | [RL-4 : Bandits Manchots et le Compromis…](../../MyIA.AI.Notebooks/RL/rl_4_multi_armed_bandits.ipynb) | BETA | Oui | +| 13 | [RL-5 : MDP, Programmation Dynamique et Q-Learning…](../../MyIA.AI.Notebooks/RL/rl_5_mdp_dp_qlearning.ipynb) | BETA | Oui | +| 14 | [RL-6 : Deep Q-Network (DQN) et Policy Gradient](../../MyIA.AI.Notebooks/RL/rl_6_dqn_policy_gradient.ipynb) | BETA | Oui | +| 15 | [RL-6b - Actor-Critic : unir valeur et politique](../../MyIA.AI.Notebooks/RL/rl_6b_actor_critic.ipynb) | BETA | Oui | +| 16 | [PPO (Proximal Policy Optimization) depuis zero](../../MyIA.AI.Notebooks/RL/rl_6c_ppo_from_scratch.ipynb) | BETA | Oui | +| 17 | [SAC (Soft Actor-Critic) depuis zero](../../MyIA.AI.Notebooks/RL/rl_6d_sac_from_scratch.ipynb) | BETA | Oui | +| 18 | [GRPO (Group Relative Policy Optimization) depuis zero](../../MyIA.AI.Notebooks/RL/rl_6e_grpo_from_scratch.ipynb) | BETA | Non | +| 19 | [RL-7 : Introduction a l'Apprentissage Multi-Agent](../../MyIA.AI.Notebooks/RL/rl_7_multi_agent_rl.ipynb) | BETA | Oui | +| 20 | [RL-8 : Model-Based RL — Dyna-Q et planification](../../MyIA.AI.Notebooks/RL/rl_8_model_based_dyna_q.ipynb) | BETA | Oui | +| 21 | [RL-9 : RL offline — Behavior Cloning et erreur…](../../MyIA.AI.Notebooks/RL/rl_9_offline_rl.ipynb) | BETA | Oui | +| 22 | [RL Post-Training — 1 : PPO pour l'alignement d'un petit…](../../MyIA.AI.Notebooks/RL/rlpt_1_ppo_lm_rlhf.ipynb) | BETA | Oui | +| 23 | [RL Post-Training — 2 : GRPO minimal — alignement d'un…](../../MyIA.AI.Notebooks/RL/rlpt_2_grpo_minimal.ipynb) | BETA | Non | +| 24 | [RL Post-Training — 3 : Reward hacking — anatomie d'un…](../../MyIA.AI.Notebooks/RL/rlpt_3_reward_hacking.ipynb) | BETA | Non | +| 25 | [RL Post-Training — 4 : DPO offline vs RL online — même…](../../MyIA.AI.Notebooks/RL/rlpt_4_dpo_vs_ppo.ipynb) | BETA | Non |