Fr. 136.00

Computational Models of Conditioning

English · Hardback

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Informationen zum Autor Dr Schmajuk is a Professor of Psychology and Neuroscience at Duke University. He has developed and tested several neural network models of classical conditioning, operant conditioning, animal communication, creativity, spatial learning, cognitive mapping and prepulse inhibition. His previous books include Animal Learning and Cognition: A Neural Network Approach (Cambridge University Press, 1997), Latent Inhibition and its Neural Substrates (Kluwer Academic, 2002), and Mechanisms in Classical Conditioning: A Computational Approach (Cambridge University Press, 2010). Klappentext Presents the latest advancements in the field of computational models of conditioning and some of their physiological bases. Zusammenfassung Mathematical models are required to describe the intricacies of classical conditioning. Their complexity puts their workings of those models beyond the ability of our intuitive thinking! and makes computer simulations irreplaceable. The latest advancements in the field of mathematical theories of conditioning and some of their physiological bases are presented. Inhaltsverzeichnis Introduction; 1. Evolution of attention in learning John K. Kruschke and Richard A. Hullinger; 2. The arguments of associations Justin A. Harris; 3. The hybrid modeling approach to conditioning Michael E. Le Pelley; 4. Within-compound associations: models and data James E. Witnauer and Ralph R. Miller; 5. Associative modulation of US processing: implications for understanding of habituation Allan R. Wagner and Edgar H. Vogel; 6. Attention, associations, and configurations in conditioning Nestor A. Schmajuk, Munir G. Kutlu, Joseph Dunsmoor and José A. Larrauri; 7. Computer simulation of the cerebellum Michael D. Mauk; 8. Towards a neural-network interpretation of the operant-respondent distinction José E. Burgos; Index.

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