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Adaptiveness in Agent Communication: Application and Adaptation of Conversation Patterns

  • Felix Fischer
  • Michael Rovatsos
  • Gerhard Weiss
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3859)

Abstract

Communication in multi-agent systems (MASs) is usually governed by agent communication languages (ACLs) and communication protocols carrying a clear cut semantics. With an increasing degree of openness, however, the need arises for more flexible models of communication that can handle the uncertainty associated with the fact that adherence to a supposedly agreed specification of possible conversations cannot be ensured on the side of other agents.

In this paper, we argue for adaptiveness in agent communication. We present a particular approach that combines conversation patterns as a generic way of describing the available means of communication in a MAS with a decisiontheoretic framework and various different machine learning techniques for applying these patterns in and adapting them from actual conversations.

Keywords

Multiagent System Markov Decision Process Agent Communication Inductive Logic Programming Interaction Protocol 
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 2006

Authors and Affiliations

  • Felix Fischer
    • 1
    • 3
  • Michael Rovatsos
    • 2
  • Gerhard Weiss
    • 3
  1. 1.Department of InformaticsUniversity of MunichMunichGermany
  2. 2.School of InformaticsUniversity of EdinburghEdinburghUK
  3. 3.Department of InformaticsTechnical University of MunichGarchingGermany

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