Reducing the complexity of multiagent reinforcement learning

Proceedings of the International Conference on Autonomous Agents

Volumn , Issue , 2007, Pages 210-212

  Burkov, Andriy ^a   Chaib Draa, Brahim ^a  

^a UNIVERSITÉ LAVAL   (Canada)

Author keywords

Initialization; Multiagent learning; Q learning; Stochastic games

Indexed keywords

CO-OPERATIVE ROBOTICS; INITIALIZATION; LEARNING COMPLEXITY; MULTI AGENTS; MULTI-AGENT REINFORCEMENT LEARNING; MULTIAGENT LEARNING; Q-LEARNING; Q-VALUES; REINFORCEMENT LEARNING ALGORITHMS; SINGLE AGENTS; STOCHASTIC GAMES;

AGENTS; AUTONOMOUS AGENTS; EDUCATION; FUZZY CLUSTERING; GAME THEORY; MULTI AGENT SYSTEMS; RANDOM PROCESSES; REINFORCEMENT; REINFORCEMENT LEARNING;

LEARNING ALGORITHMS;

EID: 60349127987     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1329125.1329178     Document Type: Conference Paper

References (3)

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2. S. Koenig and R. G. Simmons. The effect of representation and knowledge on goal-directed exploration with reinforcement-learning algorithms. Machine Learning, 22:227-250, 1996.
3. H. Young. The evolution of conventions. Econometrica, 61(1):57-84, 1993.