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Modularity in Biological Evolution and Evolutionary Computation

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Abstract

The basic principles of selectionism were transferred in a simplified form from population genetics to the field of evolutionary computation in order to solve applied problems of optimization and adaptation. Considerable practical experience has been gained for the almost half a century of development in this field of computer science, and interesting theoretical results have been obtained. One of the main properties of biological systems is modularity, which manifests itself at all levels of their organization, starting with molecular genetics and ending with entire organisms and their communities. In this survey, the phenomena and patterns associated with modularity in genetics and evolutionary computation are compared. The similarities and differences in the results from these areas of research are analyzed from the point of view of modularity, and the possibilities for sharing knowledge between them are discussed.

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Notes

  1. The objective function in mathematical optimization is understood to be a function with real values defined on a set of solutions to the optimization problem. The latter consists in the search for a solution that achieves the maximum or minimum of the objective function.

  2. The salesman’s task is to find the shortest route through all of the given cities and then return to the original city.

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Authors and Affiliations

  1. Sechenov Institute of Evolutionary Physiology and Biochemistry, Russian Academy of Sciences, St. Petersburg, Russia

    A. V. Spirov

  2. Institute of Scientific Information for Social Sciences, Russian Academy of Sciences, Moscow, Russia

    A. V. Spirov & A. V. Eremeev

  3. Sobolev Institute of Mathematics, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia

    A. V. Eremeev

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  1. A. V. Spirov
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Correspondence to A. V. Spirov or A. V. Eremeev.

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Spirov, A.V., Eremeev, A.V. Modularity in Biological Evolution and Evolutionary Computation. Biol Bull Rev 10, 308–323 (2020). https://doi.org/10.1134/S2079086420040076

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