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Authors: Alexander V. Spirov 1 and David M. Holloway 2

Affiliations: 1 The Sechenov Institute of Evolutionary Physiology and Biochemistry of the Russian Academy of Sciences and State University of New York at Stony Brook, Russian Federation ; 2 British Columbia Institute of Technology, Canada

ISBN: 978-989-8425-83-6

Keyword(s): Genetic algorithms, Recombination, Building blocks, Natural computing, Retroviral recombination.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Genetic Algorithms ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Soft Computing

Abstract: Classical understandings of biological evolution inspired creation of the entire order of Evolutionary Computation (EC) heuristic optimization techniques. In turn, the development of EC has shown how living organisms use biomolecular implementations of these techniques to solve particular problems in survival and adaptation. An example of such a natural Genetic Algorithm (GA) is the way in which a higher organism’s adaptive immune system selects antibodies and competes against its complement, the development of antigen variability by pathogenic organisms. In our approach, we use operators that implement the reproduction and diversification of genetic material in a manner inspired by retroviral reproduction and a genetic-engineering technique known as DNA shuffling. We call this approach Retroviral Genetic Algorithms, or retroGA (Spirov and Holloway, 2010). Here, we extend retroGA to include: (1) the utilization of tags in strings; (2) the capability of the Reproduction-Crossover opera tor to read these tags and interpret them as instructions; and (3), as a consequence, to use more than one reproductive strategy. We validated the efficacy of the extended retroGA technique with benchmark tests on concatenated trap functions and compared these with Royal Road and Royal Staircase functions. (More)

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Paper citation in several formats:
V. Spirov, A. and M. Holloway, D. (2011). RETROVIRAL GENETIC ALGORITHMS - Implementation with Tags and Validation Against Benchmark Functions.In Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011) ISBN 978-989-8425-83-6, pages 233-238. DOI: 10.5220/0003674102330238

@conference{ecta11,
author={Alexander V. Spirov. and David M. Holloway.},
title={RETROVIRAL GENETIC ALGORITHMS - Implementation with Tags and Validation Against Benchmark Functions},
booktitle={Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011)},
year={2011},
pages={233-238},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003674102330238},
isbn={978-989-8425-83-6},
}

TY - CONF

JO - Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011)
TI - RETROVIRAL GENETIC ALGORITHMS - Implementation with Tags and Validation Against Benchmark Functions
SN - 978-989-8425-83-6
AU - V. Spirov, A.
AU - M. Holloway, D.
PY - 2011
SP - 233
EP - 238
DO - 10.5220/0003674102330238

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