Abstract
Two binary-encoded models describing some aspects of the coevolution between an artificial immune system and a set of antigens have been proposed and analyzed. The first model has focused on the coevolution between antibodies generating gene libraries and antigens. In the second model, the coevolution involves a new population of self molecules whose function was to establish restrictions in the evolution of libraries’ population. A coevolutionary genetic algorithm (CGA) was used to form adaptive niching inspired in the Coevolutionary Shared Niching strategy. Numerical experiments and conclusions are presented.
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Forrest, S., Javornik, B., Smith, R.E., Perelson, A.S.: Using genetic algorithms to explore pattern recognition in the immune system. Evolutionary Computation 1(3), 191–211 (1993)
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© 2005 Springer-Verlag Berlin Heidelberg
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Figueredo, G.P., de Carvalho, L.A.V., Barbosa, H.J.C. (2005). Coevolutionary Genetic Algorithms to Simulate the Immune System’s Gene Libraries Evolution. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_131
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DOI: https://doi.org/10.1007/11539117_131
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28325-6
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