Using parallel computing to improve the scalability of models with BDI agents

Abstract : These last years have seen the development of several extensions of modeling platforms to include BDI agents. These extensions have allowed modelers with little knowledge in programming and artificial intelligence to develop their own cognitive agents. However, especially in large-scale simulations, the problem of the computational time required by such complex agents is still an open issue. In order to address this difficulty , we propose a parallel version of the BDI architecture integrated into the GAMA platform. We show through several case studies that this new parallel architecture is much more efficient in terms of execution time, while remaining easy to use even by non-computer scientists.
Type de document :
Communication dans un congrès
Social Simulation Conference, Sep 2017, Dublin, Ireland
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01573385
Contributeur : Patrick Taillandier <>
Soumis le : mercredi 9 août 2017 - 13:06:00
Dernière modification le : jeudi 10 août 2017 - 01:08:46

Fichier

SSC - 2017_Taillandier et al.....
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01573385, version 1

Collections

Citation

Patrick Taillandier, Mathieu Bourgais, Alexis Drogoul, Laurent Vercouter. Using parallel computing to improve the scalability of models with BDI agents. Social Simulation Conference, Sep 2017, Dublin, Ireland. <hal-01573385>

Partager

Métriques

Consultations de
la notice

63

Téléchargements du document

12