Using the opponent pass modeling method to improve defending ability of a (Robo)soccer simulation team

Abstract

Modeling agents' behavior has always been a challenge in multiagent systems. In a competitive environment, predicting future behaviors of opponents helps to make plans to confront their actions properly. We have used the RoboCup soccer server environment [1] to design a coach, capable of analyzing simulated soccer games and making decisions to improve teammate players' behavior during the games. We will introduce our "Opponent Pass Modeling" method which makes a model of opponent team's passing behavior to guard opponent players and as a result, to improve the defending behavior of our team. We will also describe a new approach to evaluate coach algorithms using soccer server log-files and LogCoach tool.