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realisation_env_grille_cqlearning_cmu_tr_ttg

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realisation_env_grille_cqlearning_cmu_tr_ttg [2025/07/03 20:43]
216.73.216.192 old revision restored (2025/07/01 03:19)
realisation_env_grille_cqlearning_cmu_tr_ttg [2025/07/06 22:08] (current)
216.73.216.208 old revision restored (2025/07/03 21:47)
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 Article utilisé : http://www.aamas-conference.org/Proceedings/aamas2010/pdf/01%20Full%20Papers/15_02_FP_0421.pdf Article utilisé : http://www.aamas-conference.org/Proceedings/aamas2010/pdf/01%20Full%20Papers/15_02_FP_0421.pdf
  
-==== Présentation ==== +Synthèse https://drive.google.com/open?id=0B7dh6En0bP-KRWdBM0VMc1ZvYjA
- +
-Le CQ-Learning permet la coordination d'agents. Son implémentation fait office de surcouche au QLearning qui rend les agents sensibles aux collisions. +
- +
-Etant donné que certaines parties de l'article cité plus haut ne sont pas claires, l'algorithme implémenté ici est peut être légèrement différent sur certains points, cependant le principe reste le même. +
- +
-==== Expérience ==== +
- +
-L'algorithme est testé sur trois environnements différents, un Tunnel to Goal (ttg) un cmu (quoi que cela puisse vouloir dire), et un Two Robots Game (tr). +
- +
-CMU +
-{{:cmu_exemple.png?500|}} +
- +
-TR +
-{{:tr_exemple.png?300|}} +
- +
-TTG +
-{{:ttg_exemple.png?300|}} +
-==== Resultats ====+
realisation_env_grille_cqlearning_cmu_tr_ttg.1751568188.txt.gz · Last modified: 2025/07/03 20:43 by 216.73.216.192