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Author Notes:

Address correspondence to J.J McDowell, Department of Psychology, Emory University, Atlanta, GA 30322 (e-mail: psyjjmd@emory.edu).



  • selection by consequences
  • matching theory
  • behavior dynamics
  • complexity theory
  • computational modeling
  • concurrent schedules

Toward a Mechanics of Adaptive Behavior: Evolutionary Dynamics and Matching Theory Statics


Journal Title:

Journal of the Experimental Analysis of Behavior


Volume 94, Number 2


, Pages 241-260

Type of Work:

Article | Post-print: After Peer Review


One theory of behavior dynamics instantiates the idea that behavior evolves in response to selection pressure from the environment in the form of reinforcement. This computational theory implements Darwinian principles of selection, reproduction, and mutation, which operate on a population of potential behaviors by means of a genetic algorithm. The behavior of virtual organisms animated by this theory may be studied in any experimental environment. The evolutionary theory was tested by comparing the steady-state behavior it generated on concurrent schedules to the description of steady state behavior provided by modern matching theory. Ensemble fits of modern matching theory that enforced its constant-k requirement and the parametric identities required by its equations, accounted for large proportions of data variance, left random residuals, and yielded parameter estimates with values and properties similar to those obtained in experiments with live organisms. These results indicate that the dynamics of the evolutionary theory and the statics of modern matching theory together constitute a good candidate for a mechanics of adaptive behavior.

Copyright information:

Society for the Experimental Analysis of Behavior, Inc.

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