Robust Evaluation of RoboCup Soccer Strategies by Using Match History

In this paper we improve the performance of an evolutionary method for obtaining team strategies in a simulated robot soccer domain. In the previous method each team strategy was evaluated based on the goals and the goals against of a single game. It is possible for a good team strategy to be eliminated from the population in the evolutionary method as there is a high degree of uncertainty in the simulated soccer game. In order to tackle the problem of uncertainty, we propose a robust evaluation method using match history. The performance of team strategies in the proposed method is measured by the average goals and average goals against. Through a series of computational experiments, we show the effectiveness of our robust evaluation method.