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

Robin Lamarche-Perrin 1 Yves Demazeau 2 Jean-Marc Vincent 3
2 MAGMA
LIG - Laboratoire d'Informatique de Grenoble
3 MESCAL - Middleware efficiently scalable
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
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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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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