Recognizing Probabilistic Opponent Movement Models

  • Patrick Riley
  • Manuela Veloso
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2377)


In multiagent adversarial domains, team agents should adapt to the environment and opponent. We introduce a model representation as part of a planning process for a simulated soccer domain. The planning is centralized, but the plans are executed in a multi-agent environment, with teammate and opponent agents. Further, we present a recognition algorithm where the model which most closely matches the behavior of the opponents can be selected from few observations of the opponent. Empirical results are presented to verify that important information is maintained through the abstraction the models provide.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Patrick Riley
    • 1
  • Manuela Veloso
    • 1
  1. 1.Computer Science DepartmentCarnegie Mellon UniversityPittsburgh

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