The Effect of Hamming Distances in a Computational Model ofSelection by Consequences Pubblico

Abstract

McDowell (2004) instantiated the Darwinian principles of selection, recombination, and mutation in a computational model of selection by consequences. The model forces a population of behaviors to evolve under the selection pressure of the environment, by applying low-level Darwinian principles; it has been tested under a variety of conditions and the quantitative outcomes are remarkably similar to those obtained in experiments with live organisms (McDowell et al., 2008). The computational model animates a virtual organism with a repertoire of 100 behaviors, represented by binary strings; this raises the specific issue of Hamming distances, the number of digits in a binary string that must be changed in order to obtain another bit string of equal length (Hamming, 1950). McDowell (2008) hypothesized that in environments that reinforce two alternatives the Hamming distance may be computationally equivalent to a changeover delay (COD). In experiments with live organisms that reinforce two alternatives, an interesting phenomenon is sometimes observed: instead of responding to the alternatives, the organism behaves "as if" switching itself is reinforced. One way to prevent this phenomenon is the use of a changeover delay, a procedure that prevents the organism from acquiring reinforcement if it switches too often (Findley, 1958). The computational model places the target classes next to each other, and, traditionally, they are separated by a large Hamming cliff, which makes it more difficult for a behavior to switch from one target class to the other. In order to investigate the effects of smaller cliffs between the target classes, they were positioned at different locations along the continuum; in addition, other parameters were systematically varied. Results confirmed McDowell et al.'s Hamming-Distance-As-Changeover-Delay hypothesis and also revealed a robust rule about the effects of Hamming distances within the model. The steady state outcome is, therefore, a product of the reiteration of Darwinian rules, and not an artifact of conveniently choosing an exceptional location for the target classes. This study constitutes another argument for the robustness of the computational model of selection by consequences as a valid account of the behavioral dynamics.

Table of Contents

I. Introduction………………………………………………………………………….3

II. General Method…………………………………………………………………….22

III. General Discussion…………………………………………………...…………….44

IV. References……………..……………….…………………………………………..49

V. Tables…………………………………………………………………………….....53

VI. Figure Captions……..………………………………………………………………58

VII. Figures……….……………………………………………………………………..67

About this Master's Thesis

Rights statement

• Permission granted by the author to include this thesis or dissertation in this repository. All rights reserved by the author. Please contact the author for information regarding the reproduction and use of this thesis or dissertation.

School	Laney Graduate School
Department	Psychology
Degree	MA
Submission	Master's Thesis
Language	English
Research Field	Psychology, Behavioral Psychology, Experimental
Parola chiave	Behavior dynamics, Hamming distance, computational theory, concurrent schedules
Committee Chair / Thesis Advisor	McDowell, Jack J, Emory University
Committee Members	Wolff, Phillip, Emory University Emory, Eugene, Emory University

Ultima modifica

Primary PDF

Thumbnail	Title	Date Uploaded	Actions
	The Effect of Hamming Distances in a Computational Model ofSelection by Consequences ()	2018-08-28 16:37:45 -0400	Press to Select an action Download

Supplemental Files

Thumbnail	Title	Date Uploaded	Actions