From Learning Theory to Connectionist Theory
Essays in Honor of William K. Estes, Volume I; From Learning Processes to Cognitive Processes, Volume II
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Product details:
- Edition number 1
- Publisher Psychology Press
- Date of Publication 1 May 1992
- ISBN 9780805810981
- Binding Paperback
- No. of pages288 pages
- Size 229x152 mm
- Weight 530 g
- Language English 0
Categories
Short description:
First Published in 1992. Routledge is an imprint of Taylor & Francis, an informa company.
MoreLong description:
These two volumes consist of chapters written by students and colleagues of W.K. Estes. The books' contributors -- themselves eminent figures in the field -- reflect on Estes' sweeping contributions to mathematical as well as cognitive and experimental psychology. As indicated by their titles, Volume I features mathematical and theoretical essays, and Volume II presents cognitive and experimental essays. Both volumes contain insightful literature reviews as well as descriptions of exciting new theoretical and empirical advances. Many of the essays also incorporate personal reminiscences reflecting the authors' fond affection for their illustrious mentor.
"...these volumes are excellent collections of articles....two fine volumes edited and written by first-rate cognitive psychologists."
&&&8212;Contemporary Psychology
Table of Contents:
Volume I: From Learning Theory to Connectionist Theory. Contents: P. Suppes, Estes' Statistical Learning Theory: Past, Present, and Future. G. Bower, E. Heit, Choosing Between Uncertain Options: A Reprise to the Estes Scanning Model. R.D. Luce, A Path Taken: Aspects of Modern Measurement Theory. J.T. Townsend, Chaos Theory: A Brief Tutorial and Discussion. S. Link, Imitatio Estes: Stimulus Sampling Origins of Weber's Law. D. LaBerge, A Mathematical Theory of Attention in a Distractor Task. J.I. Yellot, Jr., Triple Correlation and Texture Discrimination. R.M. Nosofsky, Exemplars, Prototypes, and Similarity Rules. M.A. Gluck, Stimulus Sampling and Distributed Representations in Adaptive Network Theories of Learning. B.B. Murdock, Serial Organization in a Distributed Memory Model. S.A. Sloman, D.E. Rumelhart, Reducing Interference in Distributed Memories Through Episodic Gating. J.G. Rueckl, S.M. Kosslyn, What Good is Connectionist Modeling? A Dialogue.
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