Evolving Evolvability in the Context of Environmental Change: A Gene Regulatory Network (GRN) Approach

Yifei Wang, Stephen Matthews, J J Bryson

Research output: Contribution to conferencePaper

1 Citation (Scopus)
132 Downloads (Pure)

Abstract

Evolvability is the capacity of a genotype to rapidly adjust to certain types of environmental challenges or opportunities. This capacity, documented in nature, reflects foresight enabled by the capacity of evolution to capture and represent regularities not only in extant environments, but in the ways in which the environments tend to change. Here we posit that evolvability substantially benefits from the hierarchical representations afforded by Gene Regulatory Networks (GRNs). We present an extension of standard Genetic Algorithms (GAs) and demonstrate its capacity to learn a genotype phylogeny able to express rapid phenotypic shifts in the context of an oscillating environment.
Original languageEnglish
Pages47-53
Number of pages8
DOIs
Publication statusPublished - 30 Jul 2014
EventThe 14th International Conference on the Synthesis and Simulation of Living Systems - Javits Center, New York, UK United Kingdom
Duration: 30 Jul 20142 Aug 2014

Conference

ConferenceThe 14th International Conference on the Synthesis and Simulation of Living Systems
CountryUK United Kingdom
CityNew York
Period30/07/142/08/14

Keywords

  • evolvability
  • Gene regulatory network
  • Genetic algorithms
  • evolution dynamics

ASJC Scopus subject areas

  • Artificial Intelligence

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    Wang, Y., Matthews, S., & Bryson, J. J. (2014). Evolving Evolvability in the Context of Environmental Change: A Gene Regulatory Network (GRN) Approach. 47-53. Paper presented at The 14th International Conference on the Synthesis and Simulation of Living Systems, New York, UK United Kingdom. https://doi.org/10.7551/978-0-262-32621-6-ch010