Statistical exploratory analysis of agent-based simulations in a social context

Nathalie Villa-Vialaneix, Christophe Sibertin-Blanc, Pascal Roggero

Abstract


This paper presents a case study for motivating the use of data mining in a social agent-based simulation framework. The data used in this article come from the social simulation platform SocLab. They were generated from a model designed to analyze a real situation related to the management of a river in the South West of France. Several standard statistical methods are used to analyze the possible outcomes of the discussion between the actors. Finally, a typology of these outcomes is obtained with a self-organizing map. The presentation is accessible to readers with an intermediate level of statistics.

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