Computational Model of Selection by Consequences: Patterns of Preference Change on Concurrent Schedules Pubblico

Abstract

Abstract
Computational Model of Selection by Consequences:
Patterns of Preference Change on Concurrent Schedules
The computational model of selection by consequences is an ontogenetic dynamic
account of adaptive behavior based on the Darwinian principle of selection by
consequences. The model is a virtual organism based on a genetic algorithm, a class of
computational algorithms that instantiate the principles of selection, fitness, reproduction
and mutation. The computational model has been thoroughly tested in experiments with
a variety of single alternative and concurrent schedules. A number of published reports
demonstrated that the model generated patterns of behavior that were quantitatively
equivalent to the findings from live organisms. The experiments and analyses proposed
here assess the behavior of the computational model for evidence of preference change
phenomena identified and described by Davison, Baum, and their collaborators in
concurrent schedule experiments with pigeons. Three types of preference change
behavior observed in live organisms were tested in experiments with the virtual
organism: molar and molecular effects of behavioral adjustment in rapidly changing
environment and presence of preference pulses. The results of this study provide strong
evidence in support of the selectionist account of adaptive behavior.

Table of Contents

Table of Contents
Introduction 1
Computational Model of Selection by Consequences 1
Testing the Model (2004 - present) 5
Preference Change: Molar and Molecular Patterns 8
Method 13
Subjects 13
Apparatus and Materials 13
Procedure 13
Results 16
Part I 16
Part II 20
Part III 22
Discussion 24
References 31
Appendix A 46
Appendix B 49

About this Dissertation

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School	Laney Graduate School
Department	Psychology
Subfield / Discipline	Clinical Psychology
Degree	PhD
Submission	Dissertation
Language	English
Research Field	Psychology, General
Parola chiave	concurrent schedules computational model selection by consequences adaptive behavior
Committee Chair / Thesis Advisor	McDowell, Jack J, Emory University
Committee Members	Neill, Darryl B, Emory University Marr, M. Jackson, Georgia Institute of Technology Wolff, Phillip, Emory University Emory, Eugene, Emory University

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