Animal Learning and Cognition: A Neural Network Approach (Problems in the Behavioural Sciences) [Paperback]

Nestor A. Schmajuk (Author)

Book Description

Publication Date: April 28, 1997 | ISBN-10: 0521456967 | ISBN-13: 978-0521456968 | Edition: Pap/Dskt

In this advanced text, the author, starting with the simple assumption that psychological associations are represented by the strength of synaptic connections, details several mechanistic descriptions of complex cognitive behaviors. Part I presents neural network theories of classical conditioning; Part II describes neural networks of operant conditioning, and animal communication; Part III discusses spatial and cognitive mapping, and finally, Part IV shows how neural network models permit one to simultaneously develop psychological theories and models of the brain. The book includes computer software that allows the computer simulation of classical conditioning and the effect of different brain lesions on many classical paradigms. All those people interested in neural networks, from psychologists, through neuroscientists to computer scientists working on artificial intelligence and robotics, will find this book an excellent advanced guide to the subject.

Editorial Reviews

Review

"In this new effort, Nestor Schmajuk turns the powerful tools of neural-network modeling to animal learning and cognition...[H]e is among the best and most influential modelers working in the field...This book fully qualifies as a primer for neural-network models of animal cognition." American Scientist

"Animal Learning and Cognition presents a scholarly and authoritative synthesis of learning theory and neural connectionism that is a testament to the advances made in the last twenty-five years since Rescorla and Wagner initiated the contemporary era. It will set the agenda for research in animal learning and conditioning for the next decade." Anthony Dickinson, University of Cambridge

"An encyclopedic consideration of associative learning and cognition from the perspective of contemporary mathematical models and their implementation in the brain. Learning and cognition evolve within the framework of dynamical equations linked to brain processes and physiologically plausible mechanisms. This book is possibly the most unified approach to quantitative learning theory and its neural underpinnings since Hull's 1943 Principles of Behavior." John W. Moore, University of Massachusetts, Amherst

"In this new effort, Nestor Schmajuk turns the powerful tools of neural-network modeling to animal learning and cognition....he is among the best and most influential modelers working in the field." James S. Nairne, American Scientist

Book Description

Starting with the simple assumption that psychological associations are represented by the strength of synaptic connections, this advanced text details several mechanistic descriptions of complex cognitive behaviors.

Product Details

• Paperback: 352 pages
• Publisher: Cambridge University Press; Pap/Dskt edition (April 28, 1997)
• Language: English
• ISBN-10: 0521456967
• ISBN-13: 978-0521456968
• Product Dimensions: 10 x 7.1 x 0.9 inches
• Shipping Weight: 1.5 pounds (View shipping rates and policies)
• Average Customer Review: 4.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #2,426,328 in Books (See Top 100 in Books)

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Most Helpful Customer Reviews

2 of 5 people found the following review helpful:

4.0 out of 5 stars Excellent introduction to both animal behavior and modeling, December 11, 2000

By 

CHazlett (Murrysville, Pa USA) - See all my reviews

This review is from: Animal Learning and Cognition: A Neural Network Approach (Problems in the Behavioural Sciences) (Paperback)

This book is excellent for those interested in learning about animal behavior and how to model it with neural networks. While many other books focus on neural networks unto themselves, this book's primary goal is to develop a suitable explanation of basic animal behaviors, while using biologically constrained neural network models to demonstrate their predictions and to estimate their mechanisms. These down-to-earth models not only serve to make testable predictions about behavior and the mechanisms that ought to produce them, but also foster the ability to think about problems of behavior in more carefully defined and even mathematical terms. Understanding the models in this book will also give the reader a useful tool for thinking about animal behavior in a way that brings together stimulus perception, associations, attention, imagery, and other processes.