Induced states in a decision tree constructed by Q-learning

Information Sciences

Volumn 213, Issue , 2012, Pages 39-49

  Hwang, Kao Shing ^a   Chen, Yu Jen ^b   Jiang, Wei Cheng ^b   Yang, Tsung Wen ^b  

^a NATIONAL SUN YAT SEN UNIVERSITY   (Taiwan)

^b NATIONAL CHUNG CHENG UNIVERSITY   (Taiwan)

Author keywords

CART; Critic actor model; Decision trees; Q learning; Reinforcement learning; State space partition

Indexed keywords

ACTION POLICIES; ADAPTIVE HEURISTIC CRITICS; BENCHMARK DATASETS; CART; CLASSIFICATION AND REGRESSION TREE; DISCRETE STATE SPACE; INFORMATION GAIN; LEARNING CONTROL; LONG-TERM EVALUATION; MECHATRONIC SYSTEMS; NEAR-OPTIMAL POLICIES; NEURAL NETWORK MODEL; OPTIMAL POLICIES; POLICY ITERATION; Q-LEARNING; REINFORCEMENT LEARNING METHOD; SECOND PHASE; SEQUENTIAL PROCESS; SPLITTING CRITERION; STATE AGGREGATION; STATE PARTITION; STATE SPACE; TRAINING PATTERNS; TREE GROWING; TREE INDUCTION; TREE-BASED;

CLASSIFICATION (OF INFORMATION); DECISION TREES; ESTIMATION; OPTIMIZATION; PERSONNEL TRAINING;

REINFORCEMENT LEARNING;

EID: 84863723501     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2012.06.009     Document Type: Article

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