Optimization and simplification of dynamic scripting with evolution strategy and fuzzy control in a fighting game AI

We develop a combination of evolution strategy (ES) and fuzzy control (FC) to optimize and simplify an existing dynamic scripting (DS) AI called CodeMonkey for fighting game FightingICE, recently used as a platform in international game AI competitions. One of the major issues in DS is that the user has to decide a lot of parameters whose process is not simple. In addition, a complex user-defined-action-rule set for DS is required. The purpose of our work is to automate this troublesome process and improve the performance of the DS technique. We apply (1+1)-ES with the one-fifth rule for tuning parameters and FC for easing definition of additional action rules. We verify our AI´s performance in FightingICE. The test results show that although the proposed AI does not require complex parameter and rule setting by the user, it defeats the original CodeMonkey.