Adaptive learning via selectionism and Bayesianism, Part I: Connection between the two

Neural Networks

Volumn 22, Issue 3, 2009, Pages 220-228

  Zhang, Jun ^a  

^a UNIVERSITY OF MICHIGAN   (United States)

Author keywords

Bayesian update; Gibbs Boltzman distribution; Law of effect; Linear operator model; Operant conditioning; Stochastic learning automata

Indexed keywords

BAYESIAN UPDATE; GIBBS-BOLTZMAN DISTRIBUTION; LAW OF EFFECT; LINEAR OPERATOR MODEL; OPERANT CONDITIONING; STOCHASTIC LEARNING AUTOMATA;

AUTOMATA THEORY; BAYESIAN NETWORKS; DECISION THEORY; FAULT DETECTION; GAME THEORY; LAWS AND LEGISLATION; LEARNING SYSTEMS; MATHEMATICAL OPERATORS; RANDOM PROCESSES; REINFORCEMENT; STATISTICAL TESTS; STOCHASTIC MODELS; TRANSLATION (LANGUAGES);

EDUCATION;

ACTION POTENTIAL; ADAPTIVE BEHAVIOR; ARTICLE; BAYES THEOREM; CONCEPTUAL FRAMEWORK; DECISION MAKING; DECISION THEORY; DOPAMINERGIC SYSTEM; DYNAMIC EXERCISE; EVOLUTION; HUMAN; LEARNING; LEARNING THEORY; MATHEMATICAL ANALYSIS; MESENCEPHALON; PERFORMANCE; POPULATION; PREDICTOR VARIABLE; PRIORITY JOURNAL; PROBABILITY; STOCHASTIC MODEL;

ADAPTATION, PSYCHOLOGICAL; ALGORITHMS; ANIMALS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; BRAIN; CHOICE BEHAVIOR; COMPUTER SIMULATION; CONDITIONING, OPERANT; DECISION MAKING; DOPAMINE; HUMANS; LEARNING; LIKELIHOOD FUNCTIONS; LINEAR MODELS; MODELS, NEUROLOGICAL; MODELS, PSYCHOLOGICAL; NEURAL NETWORKS (COMPUTER); PROBABILITY; PROBABILITY LEARNING; PSYCHOMOTOR PERFORMANCE; STOCHASTIC PROCESSES;

EID: 67349238173     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2009.03.018     Document Type: Article

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