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Adaptive Behavior
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Evolution of Food-Foraging Strategies for the Caribbean Anolis Lizard Using Genetic Programming

John R. Koza

Stanford University

Jonathan Roughgarden

Stanford University

James P. Rice

Stanford University Knowledge Systems Laboratory

This article describes the recently developed genetic programming paradigm that genetically breeds a population of computer programs to solve problems. The article then demonstrates, step by step, how to apply genetic programming to a problem of behavioral ecology in biology—specifically, two versions of the problem of finding an optimal food-foraging strategy for the Caribbean Anolis lizard. A simulation of the adaptive behavior of the lizard is required to evaluate each possible adaptive control strategy considered for the lizard. The foraging strategy produced by genetic programming is close to the mathematical solution for the one version for which the solution is known and appears to be a reasonable approximation of the solution for the second version of the problem.

Key Words: Optimal foraging strategy • genetic programming • genetic algorithms • lizards • crossover

Adaptive Behavior, Vol. 1, No. 2, 171-199 (1992)
DOI: 10.1177/105971239200100203
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