Genome length as an evolutionary self-adaptation

Connie Loggia Ramsey, Kenneth A. De Jong, John J. Grefenstettc, Annie S. Wu, Donald S. Burke

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

There is increasing interest in evolutionary algorithms that have variahle-length genomes and/or location independent genes. However, our understanding of such algorithms both theoretically and empirically is much less well developed than the more traditional fixed-length, fixed-location ones. Recent studies with VIV (Virtual Virus), a variable length, GA-based computational model of viral evolution, have revealed several emergent phenomena of both biological and computational interest. One interesting and somewhat surprising result is that the length of individuals in the population self-adapts in direct response to the mutation rate applied, so the GA adaptively strikes the balance it needs to successfully solve the problem. Over a broad range of mutation rates, genome length tends to increase dramatically in the early phases of evolution, and then decrease to a level based on the mutation rate. The plateau genome length (i.e., the average length of individuals in the final population) generally increases in response to an increase in the base mutation rate. Furthermore, the mutation operator rate and adapted length resulting in the best problem solving performance is about one mutation per individual. This is also the rate at which mutation generally occurs in biological systems, suggesting an optimal, or at least biologically plausible, balance of these operator rates. These results suggest that an important property of these algorithms is a considerable degree of self-adaptation.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages345-353
Number of pages9
Volume1498 LNCS
StatePublished - 1998
Event5th International Conference on Parallel Problem Solving from Nature, PPSN 1998 - Amsterdam, Netherlands
Duration: Sep 27 1998Sep 30 1998

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1498 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other5th International Conference on Parallel Problem Solving from Nature, PPSN 1998
CountryNetherlands
CityAmsterdam
Period9/27/989/30/98

Fingerprint

Self-adaptation
Genome
Genes
Mutation
Biological systems
Viruses
Evolutionary algorithms
Operator
Biological Systems
Computational Model
Virus
Evolutionary Algorithms
Tend
Gene
Decrease

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Ramsey, C. L., De Jong, K. A., Grefenstettc, J. J., Wu, A. S., & Burke, D. S. (1998). Genome length as an evolutionary self-adaptation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1498 LNCS, pp. 345-353). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1498 LNCS).

Genome length as an evolutionary self-adaptation. / Ramsey, Connie Loggia; De Jong, Kenneth A.; Grefenstettc, John J.; Wu, Annie S.; Burke, Donald S.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1498 LNCS 1998. p. 345-353 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1498 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ramsey, CL, De Jong, KA, Grefenstettc, JJ, Wu, AS & Burke, DS 1998, Genome length as an evolutionary self-adaptation. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 1498 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1498 LNCS, pp. 345-353, 5th International Conference on Parallel Problem Solving from Nature, PPSN 1998, Amsterdam, Netherlands, 9/27/98.
Ramsey CL, De Jong KA, Grefenstettc JJ, Wu AS, Burke DS. Genome length as an evolutionary self-adaptation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1498 LNCS. 1998. p. 345-353. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Ramsey, Connie Loggia ; De Jong, Kenneth A. ; Grefenstettc, John J. ; Wu, Annie S. ; Burke, Donald S. / Genome length as an evolutionary self-adaptation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1498 LNCS 1998. pp. 345-353 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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