TY  - BOOK
AU  - Schmajuk,Nestor A.
TI  - Computational models of conditioning
SN  - 9780511760402 (ebook)
AV  - BF319.5.P34 C66 2010
U1  - 153.1 22
PY  - 2010///
CY  - Cambridge
PB  - Cambridge University Press
KW  - Paired-association learning
KW  - Congresses
KW  - Cognition
KW  - Eyelid conditioning
N1  - Title from publisher's bibliographic system (viewed on 05 Oct 2015); 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 ;;; [et al.] --; 7; Computer simulation of the cerebellum; Michael D. Mauk -- 8; The operant/respondent distinction: a computational neural-network analysis; Jose; E. Burgos
N2  - Since first described, multiple properties of classical conditioning have been discovered, establishing the need for mathematical models to help explain the defining features. The mathematical complexity of the models puts our understanding of their workings beyond the ability of our intuitive thinking and makes computer simulations irreplaceable. The complexity of the models frequently results in function redundancy, a natural property of biologically evolved systems that is much desired in technologically designed products. Experts provide the latest advancements in the field and present detailed descriptions of how the models simulate conditioned behaviour and its physiological bases. It offers advanced students and researchers examples of how the models are used to analyse existing experimental results and design future experiments. This volume is of great interest to psychologists and neuroscientists, as well as computer scientists and engineers searching for ideas applicable to the design of robots that mimic animal behaviour
UR  - https://doi.org/10.1017/CBO9780511760402
ER  -