Abstract
A multi-agent based simulation aims at imitating complex phenomena or processes of the real world. For that purpose, the simulation platform has the simulated model evolve by running a virtual time and by activating agents’ behaviour at each advancement of the time. This time coherence is ensured by the scheduler. The way this scheduler manages the simulated time could affect the performance of the simulation platform. However, conventional time scheduling approaches have limitations in some cases. As a solution, the temporality model approach addresses a set of criteria that conventional approaches cannot achieve. In this paper, we show the functioning of such a scheduler as well as a demonstration of the performance advantages of this type of approach.
Supported by the Région Réunion, the L’Oréal-UNESCO for women in science fellowship and the town of Saint-Denis.
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References
Bustos-Turu, G., Dam, K.H.V., Acha, S., Shah, N.: Estimating plug-in electric vehicle demand flexibility through an agent-based simulation model. In: 2014 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), pp. 1–6. IEEE (2014)
Fujimoto, R.M.: Time management in the high level architecture. Simulation 71(6), 388–400 (1998). https://doi.org/10.1177/003754979807100604
Galler, H.P.: Discrete-time and continuous-time approaches to dynamic microsimulation reconsidered. National Centre for Social and Economic Modelling (1997)
Helleboogh, A., Holvoet, T., Weyns, D., Berbers, Y.: Extending time management support for multi-agent systems. In: Davidsson, P., Logan, B., Takadama, K. (eds.) MABS 2004. LNCS (LNAI), vol. 3415, pp. 37–48. Springer, Heidelberg (2005). https://doi.org/10.1007/978-3-540-32243-6_4
Luke, S., Cioffi-Revilla, C., Panait, L., Sullivan, K.: MASON: a new multi-agent simulation toolkit. In: Proceedings of the 2004 Swarmfest Workshop, Michigan, USA, vol. 8, pp. 316–327 (2004)
Michel, F.: Formalisme, outils et éléments méthodologiques pour la modélisation et la simulation multi-agents. (Formalism, tools and methodological elements for the modeling and simulation of multi-agents systems). Ph.D. thesis, Montpellier 2 University, France (2004). https://tel.archives-ouvertes.fr/tel-01610063
Minar, N., Burkhart, R., Langton, C., Askenazi, M., et al.: The swarm simulation system: a toolkit for building multi-agent simulations (1996)
Payet, D.: Official website of skuad (2018). http://skuad.onover.top/. Accessed 15 Jul 2018
Payet, D., Courdier, R., Ralambondrainy, T., Sébastien, N.: Le modèle à temporalité: pour un équilibre entre adéquation et optimisation du temps dans les simulations agent. In: Systemes Multi-Agents, Articulation entre l’individuel et le collectif - JFSMA 2006 - Quatorzieme journees francophones sur les systemes multi-agents, Annecy, France, 18–20 October 2006, pp. 63–76 (2006)
Ralitera, T., Ferard, M., Bustos-Turu, G., van Dam, K.H., Courdier, R.: Steps towards simulating smart cities and smart islands with a shared generic framework - a case study of London and Reunion Island. In: SMARTGREENS 2017 - Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems, Porto, Portugal, 22–24 April 2017, pp. 329–336 (2017)
Turton, I.: Open Source Approaches in Spatial Data Handling. Springer, Heidelberg (2008)
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Ralitera, T., Payet, D., Aky, N., Courdier, R. (2019). The Temporality Model Time Scheduling Approach: A Practical Application. In: Davidsson, P., Verhagen, H. (eds) Multi-Agent-Based Simulation XIX. MABS 2018. Lecture Notes in Computer Science(), vol 11463. Springer, Cham. https://doi.org/10.1007/978-3-030-22270-3_9
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DOI: https://doi.org/10.1007/978-3-030-22270-3_9
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