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.
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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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