Evolution of Human-Competitive Agents in Modern Computer Games

Modern computer games have become far more sophisticated than their ancestors. In this process the requirements to the intelligence of artificial gaming characters have become more and more complex. This paper describes an approach to evolve human-competitive artificial players for modern computer games. The agents are evolved from scratch and successfully learn how to survive and defend themselves in the game. Agents trained with standard evolution against a training partner and agents trained by coevolution are presented. Both types of agents were able to defeat or even to dominate the original agents supplied by the game. Furthermore, we have made a detailed analysis of the obtained results to gain more insight into the resulting agents.