Multiagent Simulation for Water Pollution Control
Abstract
One of the most important natural resources for the ecosystem is water. However, this feature has been suffering from the impact of pollution. To work around this problem, alternatives as Multi-Agent-Systems (MAS) can be used. From this technique, it is possible to develop virtual systems similar to reality, where the action of the agents and their consequences in the environment can be analyzed, and the results of future scenarios can be used to prevent possible problems within the system. In this paper, a MAS, called Pollution X Drone, is presented in detail. In this model, it is possible to analyze the impact of pollution on the environment, and how technologies, such as the drone, can help reduce and control pollution.
Keywords:
Multiagent Systems, Water Resources, Pollution
References
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Da Fonseca, C. N. and Dos Santos, R. (2014). Um modelo de simulação a partir do ambiente netlogo. XX Encontro Regional de Estudantes de Matemática do Sul.
Farolfi, S., Müller, J.-P., and Bonté, B. (2010). An iterative construction of multi-agent models to represent water supply and demand dynamics at the catchment level. Environmental Modelling & Software, 25(10):1130–1148.
Ferber, J. (1999). Multi-agent systems: an introduction to distributed artificial intelligence. London: Addison-Wesley.
Ghazi, S., Khadir, T., and Dugdale, J. (2014). Multi-agent based simulation of environmental pollution issues: a review. In International Conference on Practical Applications of Agents and Multi-Agent Systems, pages 13–21. Springer.
Gilbert, N. and Troitzsch, K. (2005). Simulation for the social scientist. Buckingham: Open University Press.
Novak, M. and Wilensky, U. (2006). Netlogo wolf sheep stride inheritance model. http://ccl.northwestern.edu/netlogo/models/wolfsheepstrideinheritance. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
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Published
2019-10-15
How to Cite
LEITZKE, Bruna; PEREIRA, Letiane; ADAMATTI, Diana.
Multiagent Simulation for Water Pollution Control. In: NATIONAL MEETING ON ARTIFICIAL AND COMPUTATIONAL INTELLIGENCE (ENIAC), 16. , 2019, Salvador.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 142-153.
ISSN 2763-9061.
DOI: https://doi.org/10.5753/eniac.2019.9279.
