Crossover Operators for Evolving A Team

Abstract

Cooperative co--evolutionary systems can facilitate the development of teams of heterogeneous agents. We believe that k different behavioral strategies for controlling the actions of a group of k agents can combine to form a cooperation strategy which efficiently achieves global goals. We examine the on--line adaption of behavioral strategies utilizing genetic programming. Specifically, we deal with the credit assignment problem of how to fairly split the fitness of a team to all of its participants. We present several crossover mechanisms in a genetic programming system to facilitate the evolution of more than one member in the team during each crossover operation. Our goal is to reduce the time needed to evolve a good team. 1 Introduction We have utilized genetic programming (GP) [ Koza, 1992 ] to evolve behavioral strategies which enabled a team of loosely--coupled agents to cooperatively achieve a common goal [ Haynes and Sen, 1996, Haynes et al., 1995 ] . Since they each shared ...