Building Optimal Macroscopic Representations of Complex Multi-agent Systems - Archive ouverte HAL
Chapitre D'ouvrage Année : 2014

Building Optimal Macroscopic Representations of Complex Multi-agent Systems

Résumé

The design and the 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 system’s microscopic representation. 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 to provide the experts with feedback regarding the quality of generated representations. Several evaluation techniques are applied to the spatial and temporal aggregation of an agent-based model of international relations. The information from on-line newspapers constitutes a complex microscopic representation of the agent states. Our approach is able to evaluate geographical abstractions used by the domain experts in order to provide efficient and meaningful macroscopic representations of the world global state.
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Dates et versions

hal-01263846 , version 1 (28-01-2016)

Identifiants

  • HAL Id : hal-01263846 , version 1

Citer

Robin Lamarche-Perrin, Yves Demazeau, Jean-Marc Vincent. Building Optimal Macroscopic Representations of Complex Multi-agent Systems. Ngoc Thanh Nguyen; Ryszard Kowalczyk; Juan Manuel Corchado; Javier Bajo. Transactions on Computational Collective Intelligence XV, 8670, Springer, pp.1-27, 2014, Transactions on Computational Collective Intelligence, 978-3-662-44749-9. ⟨hal-01263846⟩
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