Skip to main content

Methodological problems in evolutionary computation

Abstract

This paper critically examines a number of methodological issues of evolutionary computations. The conclusion is made that under the existing notions the evolutionary branch of AI is unlikely to go beyond search optimization methods. A number of issues, whose solution could turn evolutionary computing into the truly mainstream of development of intelligent systems, are provided.

This is a preview of subscription content, access via your institution.

References

  1. 1.

    Bogatyrev, M.Yu., Invariants and symmetries in genetic algorithms, XI natsional’naya konferentsiya po iskusstvennomu intellektu s mezhdunarodnym uchastiem KII-2008 (Proc. 12th Nat. Conf. with Int. Participation on Artificial Intellect), Dubna, 2008.

    Google Scholar 

  2. 2.

    Bukatova, I.L., Mikhasev, Yu.I., and Sharov, A.M., Teoriya i praktika evolyutsionnogo modelirovaniya (Theory and Practice of Simulated Evolution), Moscow: Nauka, 1991.

    Google Scholar 

  3. 3.

    Varshavskii, V.I. and Pospelov, D.A., Orkestr igraet bez dirizhera: razmyshleniya ob evolyutsii nekotorykh tekh nicheskikh sistem i upravlenii imi (Orchestra Plays without Conductor: Thoughts about Evolution of Some Technical Systems and Their Control), Moscow: Nauka, 1984.

    Google Scholar 

  4. 4.

    Gorban’, A.N. and Khlebopros, R.G., Demon Darvina. Ideya optimal’nosti i estestvennyi otbor (Demon of Darwin. Idea of Optimality and Natural Selection), Moscow: Nauka, 1988.

    Google Scholar 

  5. 5.

    Dawkins, R., Extended Phenotype. Long Reach of Gene New York: Oxford, 1989; Moscow: Astrel’: CORPUS, 2010.

    Google Scholar 

  6. 6.

    Dunaev, B.B., Mathematical model of biological population evolution, Kibernetika, 1990, no. 1, pp. 107–111.

    Google Scholar 

  7. 7.

    Emel’yanov, V.V., Kureichik, V.V., and Kureichik, V.M., Teoriya i praktika evolyutsionnogo modelirovaniya (Theory and Practice of Simulated Evolution), Moscow: Fizmatlit, 2003.

    Google Scholar 

  8. 8.

    Zhivotovskii, L.A., Inheritance of acquired parameters: Lamark was right, Khimiya i Zhizn’, 2003, no. 4, pp. 22–26.

    Google Scholar 

  9. 9.

    Karpov, V.E., Simulated evolution. Problems of form and content, Novosti Iskusst. Intellekta, 2003, no. 5, pp. 35–46.

    Google Scholar 

  10. 10.

    Red’ko, V.G., Models of autonomous cognitive agents - bionic reserve of artificial intellect development, XIII natsional’naya konferentsiya po iskusstvennomu intellektu s mezhdunarodnym uchastiem KII-2012 (Proc. 13th Nat. Conf. with Int. Participation on Artificial Intellect), Belgorod, 2012.

    Google Scholar 

  11. 11.

    Red’ko, V.G., Evolyutsiya, neironnye seti, intellekt. Modeli i kontseptsii evolyutsionnoi kibernetiki (Evolution, Neuron Networks, Intellect. Models and Conceptions of Evolution Cybernetics), Moscow: URSS, 2005.

    Google Scholar 

  12. 12.

    Fogel, L.J., Owens, A.J., Walsh, M.J. (1966), Artificial Intelligence through Simulated Evolution, John Wiley.

    MATH  Google Scholar 

  13. 13.

    Tsetlin, M.L., Issledovaniya po teorii avtomatov i modelirovanie biologicheskikh sistem (Researches on Automate Theory and Biological Systems Simulation), Moscow: Nauka, 1969.

    Google Scholar 

  14. 14.

    Schmalhausen, I.I., Factors of Evolution: The Theory of Stabilizing Selection, Blakiston, Philadelphia: 1949; Moscow: Nauka, 1968.

    Google Scholar 

  15. 15.

    Fogel’, L., Owens, A., and Walsh, M., Artificial Intellect through Simulated Evolution, New York: Wiley, 1966; Moscow: Mir, 1969.

    Google Scholar 

  16. 16.

    Goldberg, D.E., Genetic Algorithms in Search, Optimization and Machine Learning, Addison Wesley, 1989.

    MATH  Google Scholar 

  17. 17.

    Holland, J.H., Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence, MIT Press, Cambridge, Massachusetts, 1998.

    Google Scholar 

  18. 18.

    Koza, J.R., Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press, Cambridge, Massachusetts, 1992.

    MATH  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to V. E. Karpov.

Additional information

Original Russian Text © V.E. Karpov, 2012, published in Iskusstvennyi Intellekt i Prinyatie Reshenii, 2012, No. 4, pp. 43–50.

About this article

Cite this article

Karpov, V.E. Methodological problems in evolutionary computation. Sci. Tech.Inf. Proc. 40, 286–291 (2013). https://doi.org/10.3103/S0147688213050031

Download citation

Keywords

  • simulated evolution
  • genetic algorithms
  • artificial intelligence