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 and has been successfully exploited in the production of artificial neural networks in particular. Most recently, this has been undertaken within coevolutionary or multi-agent scenarios. This paper uses an abstract 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 basic dynamics of SAGA remain unchanged but that the rate of genome growth is affected by the degree of coevolutionary interdependence between the entities.
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Bull, L. (2005). Coevolutionary Species Adaptation Genetic Algorithms: A Continuing SAGA on Coupled Fitness Landscapes. In: Capcarrère, M.S., Freitas, A.A., Bentley, P.J., Johnson, C.G., Timmis, J. (eds) Advances in Artificial Life. ECAL 2005. Lecture Notes in Computer Science(), vol 3630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553090_33
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DOI: https://doi.org/10.1007/11553090_33
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