Evolving simple software agents: comparing genetic algorithm and genetic programming performance

This paper investigates the relative efficiency of genetic algorithms and genetic programming in evolving simple software agents. The problem domain consists of an autonomous food-gathering agent placed on a square grid of hundred cells with food units spread evenly over the grid. Initial results show that evolving the agent using GP requires less effort than with GA. Nevertheless, further investigation revealed some interesting aspects.