R-MAX - A general polynomial time algorithm for near-optimal reinforcement learning

IJCAI International Joint Conference on Artificial Intelligence

Volumn , Issue , 2001, Pages 953-958

  Brafman, Ronen I ^a   Tennenholtz, Moshe ^b,c  

^a BEN GURION UNIVERSITY OF THE NEGEV   (Israel)

^b Stanford University   (United States)

^c TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

EXPLORATION VS. EXPLOITATIONS; MODEL-BASED REINFORCEMENT LEARNING; OPTIMAL POLICIES; POLYNOMIAL-TIME; POLYNOMIAL-TIME ALGORITHMS; SINGLE CONTROLLERS; STOCHASTIC GAME; ZERO-SUM STOCHASTIC GAMES;

ARTIFICIAL INTELLIGENCE; GAME THEORY; OPTIMIZATION; POLYNOMIAL APPROXIMATION; REINFORCEMENT LEARNING;

LEARNING ALGORITHMS;

EID: 84880854156     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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