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Anticipation as a Key for Collaboration in a Team of Agents: A Case Study in Robotic Soccer.
Manuela
Veloso, Peter Stone, and Michael
Bowling.
In Proceedings of SPIE Sensor Fusion and Decentralized Control in Robotic Systems II, pp. 134–143,
SPIE, Bellingham, WA, September 1999.
[PDF]108.2kB [postscript]1.8MB
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.
@InProceedings(SPIE99,
Author="Manuela Veloso and Peter Stone and Michael Bowling",
Title="Anticipation as a Key for Collaboration in a Team of Agents: A Case Study in Robotic Soccer",
BookTitle="Proceedings of SPIE Sensor Fusion and Decentralized Control in Robotic Systems {II}",
publisher="{SPIE}",
address="Bellingham, WA",
editor="Paul S.~Schenker and Gerard T.~McKee",
pages="134--143",
year=1999, volume=3839,
month="September",
abstract={
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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