An Overview on the Termination Conditions in the Evolution of Game Bots

Evolutionary Algorithms (EAs) are frequently used as a mechanism for the optimization of autonomous agents in games (bots), but knowing when to stop the evolution, when the bots are good enough, is not as easy as it would a priori seem. The first issue is that optimal bots are either unknown (and thus unusable as termination condition) or unreachable. In most EAs trying to find optimal bots fitness is evaluated through game playing. Many times it is found to be noisy, making its use as a termination condition also complicated. This paper summarizes our previous published work where we tested several termination conditions in order to find the one that yields optimal solutions within a restricted amount of time, to allow researchers to compare different EAs as fairly as possible. To achieve this, we examined several ways of finishing an EA who is finding an optimal bot design process for a particular game, Planet Wars in this case, with the characteristics described above, determining the capabilities of every one of them and, eventually, selecting one for future designs.