Neighbourhood Detection and Rule Selection From Cellular Automata Patterns
Yang, Y.X. and Billings, S.A.
(1999)
Neighbourhood Detection and Rule Selection From Cellular Automata Patterns.
Research Report.
ACSE Research Report 742
.
Department of Automatic Control and Systems Engineering
Abstract
Using GA's to search for CA rules from spatio-temporal patterns produced in CA evolution is usually complicated and time-consuming when both the neighbourhood structure and the local rule are searched simultaneously. The complexity of this problem motivates the development of a new search which separates the neighbourhood detection from the GA search. In this paper, the neighbourhood is determined by independently selecting certain terms from a large term set on the basis of the contribution each term makes to the next state of the cell to be updated. The GA search is then started with a considerably smaller set of candidate rules per-defined by the detected neighbourhood. This approach is tested over a large set of 1-D and 2-D rules. Simulation results illustrate the efficiency of the new algorithm.
Metadata
Authors/Creators:
Yang, Y.X.
Billings, S.A.
Copyright, Publisher and Additional Information:
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