A bot is an autonomous enemy which tries to beat the human player and/or some other bots in a game. This chapter describes the design, implementation and results of a system to evolve bots inside the PC game Unreal™. The default artificial intelligence (AI) of this bot has been improved using two different evolutionary methods: genetic algorithms (GAs) and genetic programming (GP). The first one has been applied for tuning the parameters of the hard-coded values inside the bot AI code. The second method has been used to change the default set of rules (or states) that defines its behaviour. Moreover, the first approach has been considered at two levels: individual and team, performing different studies at the latter level, looking for the best cooperation scheme. Both techniques yield very good results, evolving bots (and teams) which are capable of defeating the default ones. The best results are obtained for the GA approach, since it just performs a refinement considering the default behaviour rules, while the GP method has to redefine the whole set of rules, so it is harder to get good results. This chapter presents one possibility of AI programming: building a better model from a standard one.
Evolutionary Computation: from Genetic Algorithms to Genetic Programming
