Anticipation as a Key for Collaboration in a Team of Agents: A Case Study in Robotic Soccer

We investigate teams of complete autonomous agents that can collaborate towards achieving precise objectives in an adversarial dynamic environment. We have pursued this work in the context of robotic soccer both in simulation and with real physical robots. We brieey present these two frameworks emphasizing their diierent technical challenges. Creating eeective members of a team is a challenging research problem. We rst address this issue by introducing a team architecture organization which allows for a rich task decomposition between team members. The main contribution of this paper is our introduction of an action-selection algorithm that allows for a teammate to anticipate the needs of other teammates. Anticipation is critical for maximizing the probability of successful collaboration in teams of agents. We show how our contribution applies to the two concrete robotic soccer frameworks and present controlled empirical results run in simulation. Anticipation was successfully used by both our CMUnited-98 simulator and CMUnited-98 small-robot teams in the RoboCup-98 competition. The two teams are RoboCup-98 world champions each in its own league.