Dynamically Configurable Multi-agent Simulation for Crisis Management
| Autor: | Mahdi Zargayouna, Flavien Balbo, Fabien Badeig |
|---|---|
| Přispěvatelé: | École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Département Informatique et systèmes intelligents ( FAYOL-ENSMSE), Ecole Nationale Supérieure des Mines de St Etienne, Laboratoire Hubert Curien [Saint Etienne] (LHC), Institut d'Optique Graduate School (IOGS)-Université Jean Monnet [Saint-Étienne] (UJM)-Centre National de la Recherche Scientifique (CNRS), Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/COSYS/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est |
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Delegation Process (engineering) Computer science media_common.quotation_subject Distributed computing Complex system Scheduling (production processes) Context (language use) Multi-agent environment 02 engineering and technology Crisis management Scheduling policy [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation Scheduling (computing) 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering Design process Crisis situation 020201 artificial intelligence & image processing Simulation design Autonomy media_common |
| Zdroj: | Agents and Multi-agent Systems: Technologies and Applications 2019 ISBN: 9789811386787 KES-AMSTA Smart Innovation, Systems and Technologies 13th KES International Conference 13th KES International Conference, Jun 2019, Julians, Malta. pp.343-352, ⟨10.1007/978-981-13-8679-4_28⟩ |
| DOI: | 10.1007/978-981-13-8679-4_28 |
| Popis: | International audience; Multi-agent-based simulation (MABS) is the processing of a multi-agent model of a complex system by a simulation platform that controls its execution. The objective is the understanding of the dynamic of this complex system with the experimenting of different configurations for the same multi-agent model. Following a scheduling process, an activated agent has to act according to his context, that is his current perceptible simulation state. In this paper, we propose to delegate the context computation process to the scheduling process. This approach has several advantages. The first is an optimization of the context computation, a single computation being used for several agents. The second advantage is a more configurable design process and a simplification of the reusability of agent behaviors in different simulations. The model that we propose gives a formal framework to support this context computation delegation while preserving agents’ autonomy. We describe a crisis situation to illustrate the benefits of our model and compare our approach with a classical simulation scheduling approach. |
| Databáze: | OpenAIRE |
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