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Journal ArticleDOI

Algebraic theory of recombination spaces

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TLDR
It is concluded that the algebraic approach to fitness landscape analysis can be extended to recombination spaces and provides an effective way to analyze the relative hardness of a landscape for a given recombination operator.
Abstract
A new mathematical representation is proposed for the configuration space structure induced by recombination, which we call “P-structure.” It consists of a mapping of pairs of objects to the power set of all objects in the search space. The mapping assigns to each pair of parental “genotypes” the set of all recombinant genotypes obtainable from the parental ones. It is shown that this construction allows a Fourier decomposition of fitness landscapes into a superposition of “elementary landscapes.” This decomposition is analogous to the Fourier decomposition of fitness landscapes on mutation spaces. The elementary landscapes are obtained as eigenfunctions of a Laplacian operator defined for P-structures. For binary string recombination, the elementary landscapes are exactly the p-spin functions (Walsh functions), that is, the same as the elementary landscapes of the string point mutation spaces (i.e., the hypercube). This supports the notion of a strong homomorphism between string mutation and recombination spaces. However, the effective nearest neighbor correlations on these elementary landscapes differ between mutation and recombination and among different recombination operators. On average, the nearest neighbor correlation is higher for one-point recombination than for uniform recombination. For one-point recombination, the correlations are higher for elementary landscapes with fewer interacting sites as well as for sites that have closer linkage, confirming the qualitative predictions of the Schema Theorem. We conclude that the algebraic approach to fitness landscape analysis can be extended to recombination spaces and provides an effective way to analyze the relative hardness of a landscape for a given recombination operator.

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Citations
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Journal ArticleDOI

Principles in the Evolutionary Design of Digital Circuits—Part II

TL;DR: It is argued that by studying evolved designs of gradually increasing scale, one might be able to discern new, efficient, and generalisable principles of design, which explain how to build systems which are too large to evolve.
Journal ArticleDOI

The topology of the possible: formal spaces underlying patterns of evolutionary change.

TL;DR: This paper proposes to extend the explanatory level for phenotypic evolution from fitness considerations alone to include the topological structure of phenotype space as induced by the genotype-phenotype map, and introduces the mathematical concepts and tools necessary to formalize the notion of accessibility pre-topology relative to which the authors can speak of continuity in the genotypes-phenotypes map and in evolutionary trajectories.
Book

Genetic algorithms

TL;DR: The fundamentals of encoding a ‘genotype’ in different circumstances are discussed and the mechanics of population selection and management and the choice of genetic ‘operators’ for generating new populations are described.
Journal ArticleDOI

Combinatorial Landscapes

TL;DR: This review focuses on the connections of landscape theory with algebraic combinatorics and random graph theory, where exact results are available.
Book ChapterDOI

A Comprehensive Survey on Fitness Landscape Analysis

TL;DR: Fitness landscapes are formally defined, an in-depth look at basic properties is provided and detailed explanations and examples of existing fitness landscape analysis techniques are given.
References
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Book

Computers and Intractability: A Guide to the Theory of NP-Completeness

TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
Book

Adaptation in natural and artificial systems

TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Journal ArticleDOI

No free lunch theorems for optimization

TL;DR: A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving and a number of "no free lunch" (NFL) theorems are presented which establish that for any algorithm, any elevated performance over one class of problems is offset by performance over another class.
Book

Orthogonal polynomials

Gábor Szegő