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Toward an Agent-Based and Equation-Based Coupling Framework

Authors :
HUYNH QUANG, Nghi
Drogoul, Alexis
Grignard, Arnaud
Nguyen Huu, Tri
Huynh, Xuan-Hiep
Unité de modélisation mathématique et informatique des systèmes complexes [Bondy] (UMMISCO)
Université Cadi Ayyad [Marrakech] (UCA)-Université de Yaoundé I-Université Gaston Bergé (Saint-Louis, Sénégal)-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Institut de la francophonie pour l'informatique-Université Pierre et Marie Curie - Paris 6 (UPMC)
Decision support Research for Environmental Applications and Models (DREAM)
CTU-DREAM, School of Information and Communication Technology, Cantho Univesity.-CTU-DREAM, School of Information and Communication Technology, Cantho Univesity.
Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université de Yaoundé I-Institut de la francophonie pour l'informatique-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Université Gaston Bergé (Saint-Louis, Sénégal)-Université Cadi Ayyad [Marrakech] (UCA)
Source :
France. 2016, ⟨10.1007/978-3-319-46909-6_28⟩, 2016, ⟨10.1007/978-3-319-46909-6_28⟩
Publication Year :
2016
Publisher :
HAL CCSD, 2016.

Abstract

International audience; The ecology modeling generally opposes two class of models, equations based models and multi-agents based models. Mathematical models allow predicting the long-term dynamics of the studied systems. However, the variability between individuals is difficult to represent, what makes these more suitable models for large and homogeneous populations. Multi-agent models allow representing the attributes and behavior of each individual and therefore provide a greater level of detail. In return, these systems are more difficult to analyze. These approaches have often been compared, but rarely used simultaneously. We propose a hybrid approach to couple equations models and agent-based models, as well as its implementation on the modeling platform Gama [7]. We focus on the representation of a classical theoretical epidemiological model (SIR model) and we illustrate the construction of a class of models based on it.

Details

Language :
English
Database :
OpenAIRE
Journal :
France. 2016, ⟨10.1007/978-3-319-46909-6_28⟩, 2016, ⟨10.1007/978-3-319-46909-6_28⟩
Accession number :
edsair.dedup.wf.001..1497c7206c68f33626b59351d720ff4b