Evolving Behavioral Strategies in Predators and Prey

Thomas Haynes and Sandip Sen Department of Mathematical &
Computer Sciences
The University of Tulsa
e--mail: [haynes,sandip]@euler.mcs.utulsa.edu

Abstract

The predator/prey domain is utilized to conduct research in
Distributed Artificial Intelligence.  Genetic Programing is used
to evolve behavioral strategies for the predator agents.  To
further the utility of the predator strategies, the prey
population is allowed to evolve at the same time.  The expected
competitive learning cycle did not surface.  This failing is
investigated, and a simple prey algorithm surfaces, which is
consistently able to evade capture from the predator algorithms.