AWESOME: A General Multiagent Learning Algorithm that Converges in Self-Play and Learns a Best Response Against Stationary Opponents

Proceedings, Twentieth International Conference on Machine Learning

Volumn 1, Issue , 2003, Pages 83-90

  Conitzer, Vincent ^a   Sandholm, Tuomas ^a  

^a Carnegie Mellon University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

NASH EQUILIBRIUM; STATIONARY OPPONENTS;

LEARNING ALGORITHMS; MULTI AGENT SYSTEMS; OBSERVATORIES; OPTIMIZATION; PHASE EQUILIBRIA; TECHNOLOGY TRANSFER;

LEARNING SYSTEMS;

EID: 1942421183     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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