Evaluation of Techniques for a Learning-Driven Modeling Methodology in Multiagent Simulation

  • Robert Junges
  • Franziska Klügl
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6251)


There have been a number of suggestions for methodologies supporting the development of multiagent simulation models. In this contribution we are introducing a learning-driven methodology that exploits learning techniques for generating suggestions for agent behavior models based on a given environmental model. The output must be human-interpretable. We compare different candidates for learning techniques – classifier systems, neural networks and reinforcement learning – concerning their appropriateness for such a modeling methodology.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Robert Junges
    • 1
  • Franziska Klügl
    • 1
  1. 1.Modeling and Simulation Research CenterÖrebro UniversitySweden

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