BAM learning of nonlinearly separable tasks by using an asymmetrical output function and reinforcement learning

IEEE Transactions on Neural Networks

Volumn 20, Issue 8, 2009, Pages 1281-1292

  Chartier, Sylvain ^a   Boukadoum, Mounir ^b   Amiri, Mahmood ^c  

^a UNIVERSITY OF OTTAWA   (Canada)

^b UNIVERSITÉ DU QUÉBEC À MONTRÉAL   (Canada)

^c UNIVERSITY OF TEHRAN   (Iran)

Author keywords

Bidirectional associative memory (BAM); Chaos control; Cusp catastrophe; Hybrid model; Nonlinearly separable tasks; Prior knowledge; Reinforcement learning

Indexed keywords

BIDIRECTIONAL ASSOCIATIVE MEMORY (BAM); CHAOS CONTROL; CUSP CATASTROPHE; HYBRID MODEL; NONLINEARLY SEPARABLE TASKS; PRIOR KNOWLEDGE;

ASSOCIATIVE PROCESSING; DISASTERS; EDUCATION; HYBRID SENSORS; NEURAL NETWORKS; REINFORCEMENT LEARNING;

REINFORCEMENT;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; COGNITION; COMPUTER SIMULATION; HUMAN; LEARNING; MEMORY; NONLINEAR SYSTEM; RECALL; REGRESSION ANALYSIS; REINFORCEMENT;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COGNITION; COMPUTER SIMULATION; HUMANS; LEARNING; MEMORY; MENTAL RECALL; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; REGRESSION ANALYSIS; REINFORCEMENT (PSYCHOLOGY);

EID: 68949202853     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2009.2023120     Document Type: Article

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