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The Darwinian Genetic Code: An Adaptation for Adapting?
Genetic Programming and Evolvable Machines, 2002Summary: The genetic code is a ubiquitous interface between inert genetic information and living organisms, as such it plays a fundamental role in defining the process of evolution. There have been many attempts to identify features of the code that are themselves adaptations.
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Genetics of Climate Change Adaptation
Annual Review of Genetics, 2012The rapid rate of current global climate change is having strong effects on many species and, at least in some cases, is driving evolution, particularly when changes in conditions alter patterns of selection. Climate change thus provides an opportunity for the study of the genetic basis of adaptation. Such studies include a variety of observational and
Steven J, Franks, Ary A, Hoffmann
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Adaptive Genetic Network Programming
2014 IEEE Congress on Evolutionary Computation (CEC), 2014Genetic Network Programming (GNP) is derived from Genetic Algorithm (GA) and Genetic Programming (GP), which applies evolution theory to evolve a population of directed graph to model complex systems. It has been shown that GNP can solve typical control problems, as well as many real-world problems.
Xianneng Li, Wen He, Kotaro Hirasawa
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Stress and adaptation in conservation genetics
Journal of Evolutionary Biology, 2005AbstractStress, adaptation and evolution are major concerns in conservation biology. Stresses from pollution, climatic changes, disease etc. may affect population persistence. Further, stress typically occurs when species are placed in captivity. Threatened species are usually managed to conserve their ability to adapt to environmental changes, whilst ...
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Genetic algorithms and directed adaptation
1994This paper presents a case for the value of “talkback” in genetic algorithms. Talkback is described in terms of an environmentally imprinted adaptation occurring at loci on the genotype, not expressed phenotypically but acting as control parameters for evolution.
John Coyne, Ray Paton
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2005
Natura non facit saltum R. Mauricio Theories of adaptation: what they do and don't say H.A. Orr Testing hypotheses regarding the genetics of adaptation P.C. Phillips QTL mapping and the genetic basis of adaptation: recent developments Z.-B. Zeng Sex differences in recombination and mapping adaptations P.D.
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Natura non facit saltum R. Mauricio Theories of adaptation: what they do and don't say H.A. Orr Testing hypotheses regarding the genetics of adaptation P.C. Phillips QTL mapping and the genetic basis of adaptation: recent developments Z.-B. Zeng Sex differences in recombination and mapping adaptations P.D.
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1993
Abstract One of the achievements of Darwin’s theory of evolution by natural selection was to provide an alternative explanation of adaptation, a mechanistic means by which the appearance of purposive functional design had been achieved without a designer.
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Abstract One of the achievements of Darwin’s theory of evolution by natural selection was to provide an alternative explanation of adaptation, a mechanistic means by which the appearance of purposive functional design had been achieved without a designer.
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Mapping genetic adaptations to pollution
Science, 2016Ecological Genomics Many organisms have evolved tolerance to natural and human-generated toxins. Reid et al. performed a genomic analysis of killifish, geographically separate and independent populations of which have adapted recently to severe pollution (see the Perspective by Tobler and ...
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Adapting Operator Settings in Genetic Algorithms
Evolutionary Computation, 1998In the majority of genetic algorithm implementations, the operator settings are fixed throughout a given run. However, it has been argued that these settings should vary over the course of a genetic algorithm run—so as to account for changes in the ability of the operators to produce children of increased fitness. This paper describes an investigation
Andrew Tuson, Peter Ross
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Integrated-Adaptive Genetic Algorithms
2003This paper proposes two general techniques for adapting operators in a genetic algorithm: one dynamically adjusts their rates, while the other customizes their specific way of operation. We show how these techniques can be integrated into a single evolutionary system, called Integrated-Adaptive Genetic Algorithm (IAGA).
Henri Luchian, Ovidiu Gheorghies
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