Abstract
Multi-Agent Systems (MAS) are extensively used as a tool for simulation of dynamic systems. Geosimulation is an urban phenomena approach that uses the multi-agent methodology to simulate discrete, dynamic, and event-oriented systems. Our focus in this paper is to use self-organization, specially strategies inspired by solutions from Swarm Intelligence, as well as the idea of social networks, and demonstrate their effect on learning in geosimulation agents.
References
Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, Oxford (1999)
Furtado, V., Melo, A., Menezes, R., Belchior, M.: Using self-organization in an agent framework to model criminal activity in response to police patrol routes. In: Proceedings of the 2006 Florida Artificial Intelligence Research Society Conference, Melbourne, Florida, USA. AAAI, Menlo Park (2006)
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© 2006 Springer-Verlag Berlin Heidelberg
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Melo, A., Menezes, R., Furtado, V., Coelho, A.L.V. (2006). Self-organized and Social Models of Criminal Activity in Urban Environments. In: Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2006. Lecture Notes in Computer Science, vol 4150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11839088_60
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DOI: https://doi.org/10.1007/11839088_60
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38482-3
Online ISBN: 978-3-540-38483-0
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