6 research outputs found

    CSM-427: Coarse Graining in an Evolutionary Algorithm with Recombination, Duplication and Inversion

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    A generalised form of recombination, wherein an offspring can be formed from any of the genetic material of the parents, is analysed in the context of a two-locus recombinative GA. A complete, exact solution, is derived, showing how the dynamical behaviour is radically different to that of homologous crossover. Inversion is shown to potentially introduce oscillations in the dynamics, while gene duplication leads to an asymmetry between homogeneous and heterogeneous strings. All non-homologous operators lead to allele ?diffusion? along the chromosome. We discuss how inferences from the two-locus results extend to the case of a recombinative GA with selection and more than two loci

    Exact computation of the expectation surfaces for uniform crossover along with bit-flip mutation

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    Theoretical Computer Science 545, 2014, pp.76-93,Uniform crossover and bit-flip mutation are two popular operators used in genetic algorithms to generate new solutions in an iteration of the algorithm when the solutions are represented by binary strings. We use the Walsh decomposition of pseudo-Boolean functions and properties of Krawtchouk matrices to exactly compute the expected value for the fitness of a child generated by uniform crossover followed by bit-flip mutation from two parent solutions. We prove that this expectation is a polynomial in ρ, the probability of selecting the best-parent bit in the crossover, and μ, the probability of flipping a bit in the mutation. We provide efficient algorithms to compute this polynomial for Onemax and MAX-SAT problems, but the results also hold for other problems such as NK-Landscapes. We also analyze the features of the expectation surfaces.Spanish Ministry of Science and Innovation and FEDER under contract TIN2011-28194 (the roadME project). Air Force Office of Scientific Research, Air Force Materiel Command, USAF, under grant number FA9550-11-1-0088

    Perturbation Theory and the Renormalization Group in Genetic Dynamics

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    Although much progress has been made in recent years in the theory of GAs and GP, there is still a conspicuous lack of tools with which to derive systematic, approximate solutions to their dynamics. In this article we propose and study perturbation theory as a potential tool to fill this gap. We concentrate mainly on selection-mutation systems, showing different implementations of the perturbative framework, developing, for example, perturbative expansions for the eigenvalues and eigenvectors of the transition matrix. The main focus however, is on diagrammatic methods, taken from physics, where we show how approximations can be built up using a pictorial representation generated by a simple set of rules, and how the renormalization group can be used to systematically improve the perturbation theory
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