How to Build the Best Macroscopic Description of Your Multi-Agent System?

  • Robin Lamarche-Perrin
  • Yves Demazeau
  • Jean-Marc Vincent
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7879)

Abstract

The design and debugging of large-scale MAS require abstraction tools in order to work at a macroscopic level of description. Agent aggregation provides such abstractions by reducing the complexity of the microscopic description. Since it leads to an information loss, such a key process may be extremely harmful for the analysis if poorly executed. This paper presents measures inherited from information theory to evaluate abstractions and provide the experts with feedback regarding the quality of generated descriptions. Several evaluation techniques are applied to the spatial aggregation of an agent-based model of international relations. The information from on-line newspapers constitutes a complex microscopic description of agent states. Our approach is able to evaluate geographical abstractions used by the domain experts in order to provide efficient and meaningful macroscopic descriptions of the world global state.

Keywords

Large-scale multi-agent systems agent aggregation macroscopic description information theory geographical and news analysis 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Robin Lamarche-Perrin
    • 1
    • 2
  • Yves Demazeau
    • 1
    • 3
  • Jean-Marc Vincent
    • 1
    • 4
  1. 1.Laboratoire d’Informatique de GrenobleFrance
  2. 2.Université de GrenobleFrance
  3. 3.CNRSFrance
  4. 4.Université Joseph FourierFrance

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