From Learning Theory to Connectionist Theory: Essays in Honor of William K. Estes, Volume I; From Learning Processes to Cognitive Processes, Volume II, 1st Edition (Paperback) book cover

From Learning Theory to Connectionist Theory

Essays in Honor of William K. Estes, Volume I; From Learning Processes to Cognitive Processes, Volume II, 1st Edition

Edited by Alice F. Healy, Stephen M. Kosslyn, Richard M. Shiffrin

Psychology Press

288 pages

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Paperback: 9780805810981
pub: 1992-05-01
Hardback: 9780805810974
pub: 1992-06-01
eBook (VitalSource) : 9780203763162
pub: 2013-04-15
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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."

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.

Subject Categories

BISAC Subject Codes/Headings:
PSYCHOLOGY / Experimental Psychology