Learning to reach the Pareto optimal Nash equilibrium as a team

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2557, Issue , 2002, Pages 407-418

  Verbeeck, Katja ^a   Nowé, Ann ^a   Lenaerts, Tom ^a   Parent, Johan ^a  

^a VRIJE UNIVERSITEIT BRUSSEL   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATION THEORY; GAME THEORY; MULTI AGENT SYSTEMS; PARETO PRINCIPLE; REINFORCEMENT LEARNING; STOCHASTIC SYSTEMS; TELECOMMUNICATION NETWORKS;

ACTION SPACES; COMMON INTERESTS; EXPLORATION PHASE; LIMITED COMMUNICATION; NASH EQUILIBRIA; PARETO-OPTIMAL; REINFORCEMENT LEARNING AGENT; STOCHASTIC OUTCOMES;

INTELLIGENT AGENTS;

EID: 84943265381     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/3-540-36187-1_36     Document Type: Conference Paper

References (12)

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