The automatic optimization of Cellular Automata (CA) models often requires a large number of time-consuming simulations before an acceptable solution can be found. As a result, CA optimization processes may involve significant computational resources. In this paper we investigate the possibility of speeding up a CA calibration through the approach of meta-model assisted search, which is widely used in many fields. The adopted technique relies on inexpensive surrogate functions able to approximate the fitness corresponding to the CA simulations. The calibration exercise presented here refers to SCIARA, a CA for the simulation of lava flows. According to the preliminary results, the use of meta-models enables to achieve a significant gain in computational time.

Meta-model Assisted Evolutionary Optimization of Cellular Automata: An Application to the SCIARA Model / D'Ambrosio, D.; Rongo, R.; Spataro, W.; Trunfio, Giuseppe, Andrea. - 7204:(2012), pp. 533-542. ((Intervento presentato al convegno Parallel Processing and Applied Mathematics tenutosi a Torun nel 11/09/2011-14/09/2011 [10.1007/978-3-642-31500-8_55].

Meta-model Assisted Evolutionary Optimization of Cellular Automata: An Application to the SCIARA Model

TRUNFIO, Giuseppe, Andrea
2012

Abstract

The automatic optimization of Cellular Automata (CA) models often requires a large number of time-consuming simulations before an acceptable solution can be found. As a result, CA optimization processes may involve significant computational resources. In this paper we investigate the possibility of speeding up a CA calibration through the approach of meta-model assisted search, which is widely used in many fields. The adopted technique relies on inexpensive surrogate functions able to approximate the fitness corresponding to the CA simulations. The calibration exercise presented here refers to SCIARA, a CA for the simulation of lava flows. According to the preliminary results, the use of meta-models enables to achieve a significant gain in computational time.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11388/76207
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 11
  • ???jsp.display-item.citation.isi??? 6
social impact