D'Ambrosio, Donato and Rongo, Rocco and Spataro, William and Trunfio, Giuseppe Andrea (2012) Optimizing cellular automata through a meta-model assisted memetic algorithm. In: Parallel Problem Solving from Nature (PPSN XII): 12th International Conference: proceedings: part II, 1-5 September 2012, Taormina, Italy. Berlin - Heidelberg, Springer. p. 317-326. (Lecture notes in computer science, 7492/2012). ISSN 0302-9743. ISBN 978-3-642-32963-0. eISBN 978-3-642-32964-7. Conference or Workshop Item.
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This paper investigates the advantages provided by a Meta-model Assisted Memetic Algorithm (MAMA) for the calibration of a Cellular Automata (CA) model. The proposed approach is based on the synergy between a global meta-model, based on a radial basis function network, and a local quadratic approximation of the fitness landscape. The calibration exercise presented here refers to SCIARA, a well-established CA for the simulation of lava flows. Compared with a standard Genetic Algorithm, the adopted MAMA provided much better results within the assigned computational budget.
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