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Coevolutionary species adaptation genetic algorithms: growth and mutation on coupled fitness landscapes

Bull, Larry

Authors

Lawrence Bull Larry.Bull@uwe.ac.uk
School Director (Research & Enterprise) and Professor



Abstract

The species adaptation genetic algorithm (SAGA) was introduced to facilitate the open-ended evolution of artificial systems. The approach enables genotypes to increase in length through appropriate mutation operators. Most recently, this has been undertaken within coevolutionary or multi-agent scenarios. This paper uses the abstract NKCS model of coevolution to examine the behaviour of SAGA on fitness landscapes which are coupled to those of other evolving entities to varying degrees. Results indicate that the rate of genome growth is affected by the degree of coevolutionary interdependence between the entities and that the mutation rate is critical within such systems

Citation

Bull, L. (2005, September). Coevolutionary species adaptation genetic algorithms: growth and mutation on coupled fitness landscapes. Paper presented at 2005 IEEE Congress on Eolutionary Computation, Edinburgh, UK

Presentation Conference Type Conference Paper (unpublished)
Conference Name 2005 IEEE Congress on Eolutionary Computation
Conference Location Edinburgh, UK
Start Date Sep 2, 2005
End Date Sep 4, 2005
Publication Date Jan 1, 2005
Peer Reviewed Peer Reviewed
Volume 1
Pages 559-564
Keywords genetics, genetic algorithms
Public URL https://uwe-repository.worktribe.com/output/1054139
Publisher URL http://www.ieee.org/index.html
Related Public URLs 10.1109/CEC.2005.1554732
Additional Information Title of Conference or Conference Proceedings : 2005 Congress on Evolutionary Computation