Abstract
We present a formalisation of host-parasite coevolution in Evolutionary Computation [2]. The aim is to gain a better understanding of host-parasite Genetic Algorithms (GAs) [3]. We discuss Rosin's [10] competetive theory of games, and show how it relates to host-parasite GAs. We then propose a new host-parasite optimisation algorithm based on this formalisation. The new algorithm takes into account the asymmetry of the two tasks: evolving hosts and evolving parasites. By self-adaptation the algorithm can find a suitable balance between the amount of resources spent on these two tasks. Our results show that this makes it possible to evolve optimal solutions by testing fewer candidates.
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© 1998 Springer-Verlag Berlin Heidelberg
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Olsson, B. (1998). A host-parasite genetic algorithm for asymmetric tasks. In: Nédellec, C., Rouveirol, C. (eds) Machine Learning: ECML-98. ECML 1998. Lecture Notes in Computer Science, vol 1398. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0026705
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DOI: https://doi.org/10.1007/BFb0026705
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