From Learning Theory to Cognitive Processes: Essays in Honor of W. K. Estes

From Learning Theory to Cognitive Processes: Essays in Honor of W. K. Estes

by Alice F. Healy
     
 

ISBN-10: 0805810986

ISBN-13: 9780805810981

Pub. Date: 05/28/1992

Publisher: Taylor & Francis

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

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Overview

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.

Product Details

ISBN-13:
9780805810981
Publisher:
Taylor & Francis
Publication date:
05/28/1992
Series:
Essays in Honor of William K. Estes, #2
Pages:
288
Product dimensions:
5.90(w) x 8.90(h) x 0.80(d)

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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