Abstract
A new model for the incorporation of learning with simulated evolution is presented. The model uses gene coordination networks to control gene expression. Alleles at a locus compete for expression by matching up to the network. Reinforcement is achieved through choice dynamics where gene expression will be decided by competing environmental states. The result is a epistasis model containing both plasticity and mean loci. Solutions obtained are adaptive in the sense that any changes in the environment will bring about a spontaneous self-organization in the pattern of gene expression resulting in a solution with (near) equivalent fitness. Additionally the model makes the search for structures through neutral or near neutral mutation possible. The model is tested on two standard job-shop scheduling problems which demonstrate the novelty of the approach.
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© 1999 Springer-Verlag Berlin Heidelberg
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Runarsson, T.P., Jonsson, M.T. (1999). Evolution of Gene Coordination Networks. In: McKay, B., Yao, X., Newton, C.S., Kim, JH., Furuhashi, T. (eds) Simulated Evolution and Learning. SEAL 1998. Lecture Notes in Computer Science(), vol 1585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48873-1_55
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DOI: https://doi.org/10.1007/3-540-48873-1_55
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