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Population structure increases the evolvability of genetic algorithms

✍ Scribed by Felix J. H. Hol; Xin Wang; Juan E. Keymer

Publisher: John Wiley and Sons
Year: 2012
Tongue: English
Weight: 483 KB
Volume: 17
Category: Article
ISSN: 1076-2787
DOI: 10.1002/cplx.21392

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✦ Synopsis

Abstract

Populations are shaped by the spatial structure of their environment: space organizes interactions between individuals locally, and gives rise to a global population structure. Both local and global population structures can have a profound influence on the evolutionary dynamics of a population. To characterize this influence, we use genetic algorithms with several distinct contact structures to evolve cellular automata, which perform a density classification task. We find that local contact structures (modeled as graphs with various topologies) that limit the number of breeding partners show greater evolvability than well‐mixed populations. Furthermore, we show that the evolvability of well‐mixed populations is enhanced in a metapopulation setting of coupled subpopulations. © 2012 Wiley Periodicals, Inc. Complexity, 2012

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