How to Build the Best Macroscopic Description of your Multi-agent System? Analysis of News through Spatial and Temporal Aggregation (two papers in PAAMS 2013 proceedings)

R. Lamarche-Perrin, Y. Demazeau and J.-M. Vincent. « How to Build the Best Macroscopic Description of your Multi-agent System? » In Y. Demazeau and T. Ishida (eds.), Proceedings of the 11th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS’13), vol. 7879 of LNCS/LNAI, p. 157-169. Springer-Verlag Berlin, Heidelberg, 2013.

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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R. Lamarche-Perrin, Y. Demazeau and J.-M. Vincent. « Analysis of News through Spatial and Temporal Aggregation. » In Y. Demazeau and T. Ishida (eds.), Proceedings the 11th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS’13), vol. 7879 of LNCS/LNAI, p. 296-299. Springer-Verlag Berlin, Heidelberg, 2013.

ABSTRACT. A leading topic of the GEOMEDIA project focuses on the analysis of international relations through print media. In this demo paper, we show how techniques for Multi-Agent Systems aggregation can be applied to the spatial and temporal aggregation of news. Two experiments show that the generated multi-resolution representations may draw attention to critical areas for the analysis.

KEYWORDS. Interdisciplinary project, agent-based model for social sciences, news analysis, spatial and temporal aggregation.

Télécharger l’article sur Springer Link.


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