Effects of phenotypic feedback and the coupling of genotypic and phenotypic spaces in genetic searches

Chow, Rick

doi:10.1109/cec.2004.1330863

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…Chow [5] studied the relationship between genotype space and phenotype space. In his work, Chow used a hybrid algorithm (a GA receiving feedback from a hill climber).…”

Section: Previous Workmentioning

confidence: 99%

On the Effects of Bit-Wise Neutrality on Fitness Distance Correlation, Phenotypic Mutation Rates and Problem Hardness

Poli¹,

Galván²

Foundations of Genetic Algorithms

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The effects of neutrality on evolutionary search are not fully understood. In this paper we make an effort to shed some light on how and why bit-wise neutrality -an important form of neutrality induced by a genotype-phenotype map where each phenotypic bit is obtained by transforming a group of genotypic bits via an encoding function -influences the behaviour of a mutation-based GA on functions of unitation.To do so we study how the fitness distance correlation (fdc) of landscapes changes under the effect of different (neutral) encodings. We also study how phenotypic mutation rates change as a function of the genotypic mutation rate for different encodings. This allows us to formulate simple explanations for why the behaviour of a GA changes so radically with different types of neutrality and mutation rates. Finally, we corroborate these conjectures with extensive empirical experimentation.

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“…Chow [5] studied the relationship between genotype space and phenotype space. In his work, Chow used a hybrid algorithm (a GA receiving feedback from a hill climber).…”

Section: Previous Workmentioning

confidence: 99%

On the Effects of Bit-Wise Neutrality on Fitness Distance Correlation, Phenotypic Mutation Rates and Problem Hardness

Poli¹,

Galván²

Foundations of Genetic Algorithms

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“…In [9,10], Chow proposed the use of a population of individuals that are composed by two chromosomes: a data chromosome and a mapping chromosome. The former chromosome is one that contains the genotypic expression (i.e., 0s and 1s for binary strings) whereas the latter chromosome stores bit locations as integers and these determine the position of the values of the data chromosome.…”

Section: Genotype-phenotype Mappings -Definitions and Propertiesmentioning

confidence: 99%

Neutrality in evolutionary algorithms… What do we know?

et al. 2011

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Publication informationEvolving Systems, 2 (3): 145-163Publisher Springer Abstract Over the last years, the effects of neutrality have attracted the attention of many researchers in the Evolutionary Algorithms (EAs) community. A mutation from one gene to another is considered as neutral if this modification does not affect the phenotype. This article provides a general overview on the work carried out on neutrality in EAs. Using as a framework the origin of neutrality and its study in different paradigms of EAs (e.g., Genetic Algorithms, Genetic Programming), we discuss the most significant works and findings on this topic. This work points towards open issues, which the community needs to address.

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Effects of phenotypic feedback and the coupling of genotypic and phenotypic spaces in genetic searches

Cited by 2 publications

References 6 publications

On the Effects of Bit-Wise Neutrality on Fitness Distance Correlation, Phenotypic Mutation Rates and Problem Hardness

On the Effects of Bit-Wise Neutrality on Fitness Distance Correlation, Phenotypic Mutation Rates and Problem Hardness

Neutrality in evolutionary algorithms… What do we know?

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