A new Q-learning algorithm based on the metropolis criterion

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 34, Issue 5, 2004, Pages 2140-2143

  Guo, Maozu ^a   Liu, Yang ^a   Malec, Jacek ^b  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b LUND UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

COMBINATORIAL MATHEMATICS; LEARNING ALGORITHMS; OPTIMIZATION; SIMULATED ANNEALING; THEOREM PROVING;

BOLTZMANN EXPLORATION; METROPOLIS CRITERION; Q-LEARNING ALGORITHM; Q-LEARNING EXPLOITATION; REINFORCEMENT LEARNING;

LEARNING SYSTEMS;

ALGORITHM; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; EVALUATION; INFORMATION RETRIEVAL; LETTER; METHODOLOGY; THEORETICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; INFORMATION STORAGE AND RETRIEVAL; MODELS, THEORETICAL;

EID: 4844223639     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2004.832154     Document Type: Article

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