Continuous-state reinforcement learning with fuzzy approximation

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

Volumn 4865 LNAI, Issue , 2008, Pages 27-43

  Buşoniu, Lucian ^a   Ernst, Damien ^b   De Schutter, Bart ^a   Babuška, Robert ^a  

^a DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

^b SUPELEC Campus de Rennes   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE SYSTEMS; AGENTS; ALGORITHMS; APPROXIMATION ALGORITHMS; CONTROL THEORY; EDUCATION; FUZZY CONTROL; INTELLIGENT AGENTS; ITERATIVE METHODS; LEARNING ALGORITHMS; LEARNING SYSTEMS; POLYNOMIAL APPROXIMATION; REINFORCEMENT; REINFORCEMENT LEARNING;

ADAPTIVE AGENTS; DISCRETE SETS; ENVIRONMENT STATES; EUROPEAN; FUZZY APPROXIMATIONS; FUZZY REPRESENTATIONS; LEARNING AGENTS; LEARNING PARADIGMS; MODEL-BASED; MODEL-FREE; MULTI-AGENT LEARNING; Q VALUES; Q-LEARNING; SIMULATION EXAMPLE;

MULTI AGENT SYSTEMS;

EID: 49949101369     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-77949-0_3     Document Type: Conference Paper

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