Experience-based reinforcement learning to acquire effective behavior in a multi-agent domain

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1886 LNAI, Issue , 2000, Pages 125-135

  Arai, Sachiyo ^a   Sycara, Katia ^a   Payne, Terry R ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INTELLIGENT AGENTS; MACHINE LEARNING; MONTE CARLO METHODS; PROFITABILITY; REINFORCEMENT LEARNING; WAGES; ARTIFICIAL INTELLIGENCE; COMPENSATION (PERSONNEL); MULTI AGENT SYSTEMS;

EFFECTIVE BEHAVIORS; MULTI AGENT; NON-COMBATANT EVACUATION; PROFIT SHARING; Q-LEARNING APPROACH; REINFORCEMENT LEARNING APPROACH; REINFORCEMENT LEARNING METHOD; SUBGOALS;

MULTI AGENT SYSTEMS; REINFORCEMENT LEARNING;

EID: 84867798807     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44533-1_16     Document Type: Conference Paper

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