Peter Stone's Selected Publications

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Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer

Peter Stone. Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer, MIT Press, 2000.
A book based on my Ph.D. thesis
Contents, availability, and on-line appendices
ISBN: 0262194384

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Abstract

This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems. First, it describes an architecture within which a flexible team structure allows member agents to decompose a task into flexible roles and to switch roles while acting. Second, it presents layered learning, a general-purpose machine-learning method for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable with existing machine-learning methods. Third, the book introduces a new multiagent reinforcement learning algorithm--team-partitioned, opaque-transition reinforcement learning (TPOT-RL)--designed for domains in which agents cannot necessarily observe the state-changes caused by other agents' actions. The final contribution is a fully functioning multiagent system that incorporates learning in a real-time, noisy domain with teammates and adversaries--a computer-simulated robotic soccer team. Peter Stone's work is the basis for the CMUnited Robotic Soccer Team, which has dominated recent RoboCup competitions. RoboCup not only helps roboticists to prove their theories in a realistic situation, but has drawn considerable public and professional attention to the field of intelligent robotics. The CMUnited team won the 1999 Stockholm simulator competition, outscoring its opponents by the rather impressive cumulative score of 110-0.

BibTeX Entry

@book(Stone:thesisbook,
        Author="Peter Stone",
        title="Layered Learning in Multiagent Systems: {A} Winning Approach to Robotic Soccer", 
        publisher="MIT Press",
        year="2000",
        abstract={
                  This book looks at multiagent systems that consist
                  of teams of autonomous agents acting in real-time,
                  noisy, collaborative, and adversarial
                  environments. The book makes four main contributions
                  to the fields of machine learning and multiagent
                  systems.
                  First, it describes an architecture within which a
                  flexible team structure allows member agents to
                  decompose a task into flexible roles and to switch
                  roles while acting. Second, it presents layered
                  learning, a general-purpose machine-learning method
                  for complex domains in which learning a mapping
                  directly from agents' sensors to their actuators is
                  intractable with existing machine-learning
                  methods. Third, the book introduces a new multiagent
                  reinforcement learning algorithm--team-partitioned,
                  opaque-transition reinforcement learning
                  (TPOT-RL)--designed for domains in which agents
                  cannot necessarily observe the state-changes caused
                  by other agents' actions. The final contribution is
                  a fully functioning multiagent system that
                  incorporates learning in a real-time, noisy domain
                  with teammates and adversaries--a computer-simulated
                  robotic soccer team.
                  Peter Stone's work is the basis for the CMUnited
                  Robotic Soccer Team, which has dominated recent
                  RoboCup competitions. RoboCup not only helps
                  roboticists to prove their theories in a realistic
                  situation, but has drawn considerable public and
                  professional attention to the field of intelligent
                  robotics. The CMUnited team won the 1999 Stockholm
                  simulator competition, outscoring its opponents by
                  the rather impressive cumulative score of 110-0.
        },
        wwwnote={A book based on my <a href="http://reports-archive.adm.cs.cmu.edu/anon/1998/abstracts/98-187.html">Ph.D. thesis</a><br>
                 <a href="http://www.cs.utexas.edu/users/pstone/book">Contents, availability, and on-line appendices</a><br>
                 ISBN: 0262194384
        },
)

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