Analysis of Multi-Robot Play Effectiveness and of Distributed Incidental Play Recognition

Distributed play-based approaches have been proposed as an effective means of switching strategies during the course of timed, zero-sum games, such as robot soccer. In this paper, we empirically show that different plays have a significant effect on opponent performance in real robot soccer games. We also consider the problem of distributed play recognition: classifying the strategy being played by the opponent team. Play recognition in real robot soccer is a particularly challenging problem because our observations are only “incidental” — that is, the primary task of our team is to play soccer, not to explicitly observe members of the other team. Despite these challenges, we achieve high classification accuracy in the robot soccer domain.