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 briefly present these two frameworks emphasizing their different technical challenges. Creating effective members of a team is a challenging research problem. We first 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 recent 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 present our team organization architecture and the anticipation algorithm. We show how our contribution applies to the two concrete robotic soccer frameworks. Anticipation was used in both our CMUnited-98 simulator and CMUnited-98 small-robot teams in the RoboCup-98 competition held jointly with ICMAS in July 1998. The two teams are RoboCup world champions each in its own league. Anticipation was one of major differences between our team and the other teams.

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In Proceedings of SPIE Sensor Fusion and Decentralized Control in Robotic Systems II, Paul S. Schenker and Gerard T. McKee (Eds.), Vol. 3839, pp. 134-143, Bellingham, WA, September 1999. SPIE.

@InProceedings{SPIE99, title={Anticipation as a Key for Collaboration in a Team of Agents: A Case Study in Robotic Soccer}, author={Manuela Veloso and Peter Stone and Michael Bowling}, booktitle={Proceedings of SPIE Sensor Fusion and Decentralized Control in Robotic Systems II}, volume={3839}, month={September}, editor={Paul S. Schenker and Gerard T. McKee}, address={Bellingham, WA}, publisher={SPIE}, pages={134-143}, url="http://www.cs.utexas.edu/users/ai-lab?SPIE99", year={1999} }