Abstract
The subject of the paper is a cellular automata with evolutionary transition functions, applied in urban context.
Using a cellular automata to describe a phenomenon, the defmition of the model consists in building the local transition rules; this process may be supported by a machine learning tool like a Learning Classifiers System.
This paper shows some simulations of learning of simple urban interaction rules.
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© 1997 Springer-Verlag Berlin Heidelberg
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Papini, L., Rabino, G.A. (1997). An Evolutionary Urban Cellular Automata: The Model and Some First Simulations. In: Conte, R., Hegselmann, R., Terna, P. (eds) Simulating Social Phenomena. Lecture Notes in Economics and Mathematical Systems, vol 456. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-03366-1_28
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DOI: https://doi.org/10.1007/978-3-662-03366-1_28
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