Examining the Impact of Neutral Theory on Genetic Algorithm Population Evolution

Seamus Hill, Colm O'Riordan

2015

Abstract

This paper examines the introduction of neutrality as proposed by Kimura (Kimura, 1968) into the genotype-phenotype mapping of a Genetic Algorithm (GA). The paper looks at the evolution of both a simple GA (SGA) and a multi-layered GA (MGA) incorporating a layered genotype-phenotype mapping based on the biological concepts of Transcription and Translation. Previous research in comparing GAs often use performance statistics; in this paper an analysis of population dynamics is used for comparison. Results illustrate that the MGA population’s evolution trajectory is quite different to that of the SGA population over dynamic landscapes and that the introduction of neutrality implicitly maintains genetic diversity within the population primarily through genetic drift in association with selection.

References

  1. Ebner, M., Langguth, P., Albert, J., Shackleton, M., and Shipman, R. (2001). On neutral networks and evolvability. In IEEE Congress on Evolutionary Computation (CEC). IEEE Press.
  2. Goldberg, D. E. and Smith, R. E. (1987). Nonstationary function optimization using genetic algorithm with dominance and diploidy. In Proceedings of the Second International Conference on Genetic Algorithms on Genetic Algorithms and Their Application, pages 59-68, Hillsdale, NJ, USA. L. Erlbaum Associates Inc.
  3. Grefenstette, J. J. and Cobb, H. G. (1993). Genetic algorithms for tracking changing environments. In Proc. of the 5th Int. Conf. on Genetic Algorithms and their Applications, pages 523-530. Morgan Kaufmann.
  4. Huynen, M. (1996). Exploring phenotype space through neutral evolution. Mol Evol, 43:165-169.
  5. Huynen, M., Stadler, P. F., and Fontana, W. (1996). Smoothness within ruggedness: the role of neutrality in adaptation. Proc Natl Acad Sci U S A., 93(1):397-401.
  6. Kimura, M. (1968). Evolutionary Rate at the Molecular Level. Nature, 217(1):624-626.
  7. Kimura, M. (1983). The Neutral Theory of Molecular Evolution. Cambridge University Press.
  8. King, J. L. and Dukes, T. H. (1969). Non-Darwinian Evolution. Science, 164:788-798.
  9. Kubalik, J. (2005). Using genetic algorithms with realcoded binary representation for solving non-stationary problems. In Ribeiro, B., Albrecht, R. F., Dobnikar, A., Pearson, D. W., and Steele, N., editors, Adaptive and Natural Computing Algorithms, pages 222-225. Springer Vienna.
  10. Morrison, R. W. and DeJong, K. A. (2002). Measurement of population diversity. In In 5th International Conference EA, 2001, volume 2310 of Incs. Springer.
  11. Schuster, P. (1997). Genotypes with Phenotypes: adventutes in an RNA toy world. Biophys Chem, 66(2):75- 110.
  12. Schuster, P., Fontana, W., Stadler, P. F., and Hofacker, I. L. (1994). From sequences to shapes and back: a case study in RNA secondary structures. Proc R Soc Lond B Biol Sci, 255(1344):279-284.
  13. Toussaint, M. (2003a). Demonstrating the evolution of complex genetic representations: An evolution of artificial plants. In In Proceedings of the 2003 Genetic and Evolutionary Computation Conference (GECCO 2003), pages 86-97. Springer-Verlag.
  14. Toussaint, M. (2003b). On the evolution of phenotypic exploration distributions. In DeJong, K. A., Poli, R., and Rowe, J., editors, Foundations of Genetic Algorithms 7 (FOGA VII), pages 169-182. Morgan Kaufmann.
  15. Toussaint, M. and Igel, C. (2002). Neutrality: A necessity for self-adaptation. In In Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2002), pages 1354-1359.
  16. Wagner, G. P. and Altenberg, L. (1996). Complex adaptations and the evolution of evolvability. Evolution, 50(3):967-976.
  17. Whitley, L. D. (1991a). Fundamental principles of deception in genetic search. In Rawlins, G. J., editor, Foundations of genetic algorithms, pages 221-241. Morgan Kaufmann, San Mateo, CA.
  18. Whitley, L. D. (1991b). Fundamental principles of deception in genetic search. In Foundations of Genetic Algorithms, pages 221-241. Morgan Kaufmann.
  19. Yang, S. (2006). On the design of diploid genetic algorithms for problem optimization in dynamic environments. In Evolutionary Computation, 2006. CEC 2006. IEEE Congress on, pages 1362-1369.
Download


Paper Citation


in Harvard Style

Hill S. and O'Riordan C. (2015). Examining the Impact of Neutral Theory on Genetic Algorithm Population Evolution . In Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA, ISBN 978-989-758-157-1, pages 196-203. DOI: 10.5220/0005594301960203


in Bibtex Style

@conference{ecta15,
author={Seamus Hill and Colm O'Riordan},
title={Examining the Impact of Neutral Theory on Genetic Algorithm Population Evolution},
booktitle={Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,},
year={2015},
pages={196-203},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005594301960203},
isbn={978-989-758-157-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,
TI - Examining the Impact of Neutral Theory on Genetic Algorithm Population Evolution
SN - 978-989-758-157-1
AU - Hill S.
AU - O'Riordan C.
PY - 2015
SP - 196
EP - 203
DO - 10.5220/0005594301960203