Abstract
We develop a new adaptive learning evolutionary algorithm - parallel transposon element technique (PTET). This algorithm is based on invasion of evolving genomes by parasitic/selfish mobile genetic elements. PTET uses island model, where multiple independent subpopulations each run a steady-state genetic algorithm (GA) on different processors and occasionally fit strings migrate between the subpopulations. We studied the efficiency of new technique on classical test problem - the John Muir Ant's Trail experiment. This problem is a behaviour algorithm and can be tested both for smooth and rugged and/or multiply connected fitness landscapes.
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© 1998 Springer-Verlag Berlin Heidelberg
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Spirov, A.V., Kadyrov, A.S. (1998). Transposon element technique applied to GA-based John Muir's trail test. In: Sloot, P., Bubak, M., Hertzberger, B. (eds) High-Performance Computing and Networking. HPCN-Europe 1998. Lecture Notes in Computer Science, vol 1401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0037235
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DOI: https://doi.org/10.1007/BFb0037235
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