Comparative Analysis between Multi-Agent Simulation Tools
Abstract
The use of tools to assist in the process of modeling and developing simulations is very important, since it streamlines the whole process as well as tends to minimize errors. In this way, their study and analysis are for choosing the tool that best suits a simulation. This paper presents a comparative study between three multiagent simulation tools, JADE, MESA and CORMAS, applied to the same problem. The objective is to present a description of each tool, develop the same application in each tool and run simulations. The entire development process until execution is used for comparative purposes in different parameters.
References
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Bellifemine, F., Caire, G., Trucco, T., and Rimassa, G. (2002). Jade programmer’s guide. Jade version, 3:13–39.
Bellifemine, F., Poggi, A., and Rimassa, G. (2000). Developing multi-agent systems with jade. In International Workshop on Agent Theories, Architectures, and Languages, pages 89–103. Springer.
Bellifemine, F., Poggi, A., and Rimassa, G. (2001). Jade: a fipa2000 compliant agent development environment. In Proceedings of the fifth international conference on Autonomous agents, pages 216–217. ACM.
Bommela, P., Becuc, N., Le Pageb, C., Bousquetb, F., and Leclercb, G. (2017). Cormas, una plataforma multiagente para la modelización interactiva.
Bousquet, F., Bakam, I., Proton, H., and Le Page, C. (1998). Cormas: common-pool resources and multi-agent systems. In International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, pages 826–837. Springer.
Castle, C. J. and Crooks, A. T. (2006). Principles and concepts of agent-based modelling for developing geospatial simulations.
Gilbert, N. and Troitzsch, K. G. (2005). PSimulation for the Social Scientist. Open University Press Milton Keynes, UK.
Masad, D. and Kazil, J. (2015). Mesa: an agent-based modeling framework. In 14th PYTHON in Science Conference, pages 53–60.
Pérez, F. and Granger, B. E. (2007). Ipython: a system for interactive scientific computing. Computing in Science & Engineering, 9(3):21–29.
Sichman, J. S., Bousquet, F., and Davidsson, P. (2003). Multi-agent-based simulation ii: Third international workshop, mabs 2002. Lecture Notes in Artificial Intelligence. Springer.
Adamatti, D. F., Sichman, J. S., and Coelho, H. (2007). Utilizaç ao de rpg e mabs no desenvolvimento de sistemas de apoioa decisao em grupos. Anais do IV Simpósio Brasileiro de Sistemas Colaborativos SBSC 2007, page 15.
Bellifemine, F., Caire, G., Trucco, T., and Rimassa, G. (2002). Jade programmer’s guide. Jade version, 3:13–39.
Bellifemine, F., Poggi, A., and Rimassa, G. (2000). Developing multi-agent systems with jade. In International Workshop on Agent Theories, Architectures, and Languages, pages 89–103. Springer.
Bellifemine, F., Poggi, A., and Rimassa, G. (2001). Jade: a fipa2000 compliant agent development environment. In Proceedings of the fifth international conference on Autonomous agents, pages 216–217. ACM.
Bommela, P., Becuc, N., Le Pageb, C., Bousquetb, F., and Leclercb, G. (2017). Cormas, una plataforma multiagente para la modelización interactiva.
Bousquet, F., Bakam, I., Proton, H., and Le Page, C. (1998). Cormas: common-pool resources and multi-agent systems. In International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, pages 826–837. Springer.
Castle, C. J. and Crooks, A. T. (2006). Principles and concepts of agent-based modelling for developing geospatial simulations.
Gilbert, N. and Troitzsch, K. G. (2005). PSimulation for the Social Scientist. Open University Press Milton Keynes, UK.
Masad, D. and Kazil, J. (2015). Mesa: an agent-based modeling framework. In 14th PYTHON in Science Conference, pages 53–60.
Pérez, F. and Granger, B. E. (2007). Ipython: a system for interactive scientific computing. Computing in Science & Engineering, 9(3):21–29.
Sichman, J. S., Bousquet, F., and Davidsson, P. (2003). Multi-agent-based simulation ii: Third international workshop, mabs 2002. Lecture Notes in Artificial Intelligence. Springer.
Published
2019-05-02
How to Cite
MACHADO, Ricardo A.; SILVEIRA, Gíulia B.; MELO, Marla P.; ADAMATTI, Diana F.; BILLA, Cleo Z..
Comparative Analysis between Multi-Agent Simulation Tools. In: WORKSHOP-SCHOOL ON AGENTS, ENVIRONMENTS, AND APPLICATIONS (WESAAC), 13. , 2019, Florianópolis/SC.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 14-24.
ISSN 2326-5434.
DOI: https://doi.org/10.5753/wesaac.2019.33336.
