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Reports (Research Report) Year : 2013

How to Build the Best Macroscopic Description of your Multi-agent System? Application to News Analysis of International Relations

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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 microscopic description complexity. Since it leads to an information loss, such a key process may be extremely harmful if poorly executed. This research report presents measures inherited from information theory (Kullback-Leibler divergence and Shannon entropy) to evaluate ab- stractions and to provide the experts with feedbacks regarding the generated descriptions. Several evaluation techniques are applied to the spatial aggregation of an agent-based model of international rela- tions. The information from on-line newspapers constitutes a complex microscopic description of agent states. Our approach is able to evalu- ate geographical abstractions used by experts and to deliver them with e cient and meaningful macroscopic descriptions of the world state.
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Dates and versions

hal-00947933 , version 1 (17-02-2014)

Identifiers

  • HAL Id : hal-00947933 , version 1

Cite

Robin Lamarche-Perrin, Yves Demazeau, Jean-Marc Vincent. How to Build the Best Macroscopic Description of your Multi-agent System? Application to News Analysis of International Relations. [Research Report] RR-LIG-035, 2013, pp.18. ⟨hal-00947933⟩
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