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

Yifei Wang; Stephen Matthews; J J Bryson

doi:10.7551/978-0-262-32621-6-ch010

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

Yifei Wang, Stephen Matthews, J J Bryson

University of Bristol

Research output: Contribution to conference › Paper › peer-review

2 Citations (SciVal)

231 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 language	English
Pages	47-53
Number of pages	8
DOIs	https://doi.org/10.7551/978-0-262-32621-6-ch010
Publication status	Published - 30 Jul 2014
Event	The 14th International Conference on the Synthesis and Simulation of Living Systems - Javits Center, New York, UK United Kingdom Duration: 30 Jul 2014 → 2 Aug 2014

Conference

Conference	The 14th International Conference on the Synthesis and Simulation of Living Systems
Country/Territory	UK United Kingdom
City	New York
Period	30/07/14 → 2/08/14

Keywords

evolvability
Gene regulatory network
Genetic algorithms
evolution dynamics

ASJC Scopus subject areas

Artificial Intelligence

Access to Document

10.7551/978-0-262-32621-6-ch010

YWangALife14-v2Accepted author manuscript, 3.4 MB

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AU - Matthews, Stephen

AU - Bryson, J J

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N2 - 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.

AB - 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.

KW - evolvability

KW - Gene regulatory network

KW - Genetic algorithms

KW - evolution dynamics

UR - http://mitpress.mit.edu/books/artificial-life-14

UR - http://dx.doi.org/10.7551/978-0-262-32621-6-ch010

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DO - 10.7551/978-0-262-32621-6-ch010

M3 - Paper

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EP - 53

T2 - The 14th International Conference on the Synthesis and Simulation of Living Systems

Y2 - 30 July 2014 through 2 August 2014

ER -

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

Abstract

Conference

Keywords

ASJC Scopus subject areas

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