Optimizing cellular automata through a meta-model assisted memetic algorithm

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.

Full text not available from this repository.

DOI: 10.1007/978-3-642-32964-7_32

Abstract

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.

Item Type:	Conference or Workshop Item (Paper)
ID Code:	7974
Status:	Published
Uncontrolled Keywords:	Cellular Automata, Model Calibration, Meta-modelling, Memetic Algorithms
Subjects:	Area 09 - Ingegneria industriale e dell'informazione > ING-INF/05 Sistemi di elaborazione delle informazioni
Divisions:	001 Università di Sassari > 01-a Nuovi Dipartimenti dal 2012 > Architettura, Design e Urbanistica
Publisher:	Springer
ISSN:	0302-9743
ISBN:	978-3-642-32963-0
ISBN:	978-3-642-32964-7
Deposited On:	20 Sep 2012 10:38

I documenti depositati in UnissResearch sono protetti dalle leggi che regolano il diritto d'autore

Repository Staff Only: item control page