A COMPUTATIONAL THEORY OF SELECTION BY CONSEQUENCES APPLIED TO CONCURRENT SCHEDULES

• Authors: Jack J McDowell, Emory University; Marcia L Caron, Emory University; Saule Kulubekova, Emory University; John P Berg, Emory University
• Journal Title: Journal of the Experimental Analysis of Behavior
• Volume: Volume 90, Number 3
• Publisher: Society for the Experimental Analysis of Behavior | 2008-11, Pages 387-403
• Type of Work: Article | Post-print: After Peer Review
• Publisher DOI: http://doi.org/10.1901/jeab.2008.90-387
• Subjects: Psychology, General; Psychology, Behavioral; Psychology, Experimental
• Keywords: selection by consequences; behavior dynamics; matching theory; computational modelling; concurrent schedules

Abstract

Virtual organisms animated by a computational theory of selection by consequences responded on symmetrical and asymmetrical concurrent schedules of reinforcement. The theory instantiated Darwinian principles of selection, reproduction, and mutation such that a population of potential behaviors evolved under the selection pressure exerted by reinforcement from the environment. The virtual organisms' steady-state behavior was well described by the power function matching equation, and the parameters of the equation behaved in ways that were consistent with findings from experiments with live organisms. Together with previous research on single-alternative schedules (McDowell, 2004; McDowell & Caron, 2007) these results indicate that the equations of matching theory are emergent properties of the evolutionary dynamics of selection by consequences.