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Integration of Advice in an Action-Selection Architecture

  • Paul Carpenter
  • Patrick Riley
  • Manuela M. Veloso
  • Gal A. Kaminka
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2752)

Abstract

The introduction of a coach competition in the RoboCup-2001 simulation league raised many questions concerning the development of a “coachable” team. This paper addresses the issues of dealing with conflicting advice and knowing when to listen to advice. An action-selection architecture is proposed to support the integration of advice into an agent’s set of beliefs. The results from the coach competition are discussed and provide a basis for experiments. Results are provided to support the claim that the architecture is well-suited for such a task.

Keywords

Behavior Manager Priority Level Primitive Action Root Behavior Hierarchical Mixture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Paul Carpenter
    • 1
  • Patrick Riley
    • 1
  • Manuela M. Veloso
    • 1
  • Gal A. Kaminka
    • 1
  1. 1.Department of Computer ScienceCarnegie Mellon UniversityPittsburghUSA

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