Foundations of Genetic Algorithms 1995 (FOGA 3)

Foundations of Genetic Algorithms 1995 (FOGA 3)

1st Edition - March 7, 1994

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  • Editor: FOGA
  • eBook ISBN: 9781483295022

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Foundations of Genetic Algorithms, 3 focuses on the principles, methodologies, and approaches involved in the integration of genetic algorithm into mainstream mathematics, as well as genetic operators, genetic programming, and evolutionary algorithms. The selection first offers information on an experimental design perspective on genetic algorithms; schema theorem and price's theorem; and fitness variance of formae and performance prediction. Discussions focus on representation-independent recombination, representation-independent mutation and hill-climbing, recombination and the re-emergence of schemata, and Walsh transforms and deception. The publication then examines the troubling aspects of a building block hypothesis for genetic programming and order statistics for convergence velocity analysis of simplified evolutionary algorithms. The manuscript ponders on stability of vertex fixed points and applications; predictive models using fitness distributions of genetic operators; and modeling simple genetic algorithms for permutation problems. Topics include exact models for permutations, fitness distributions of genetic operators, predictive model based on linear fitness distributions, and stability in the simplex. The book also takes a look at the role of development in genetic algorithms and productive recombination and propagating and preserving schemata. The selection is a dependable source of data for mathematicians and researchers interested in genetic algorithms.

Table of Contents

  • Introduction

    Part 1: Schema Based Analyses

    An Experimental Design Perspective on Genetic Algorithms

    The Schema Theorem and Price's Theorem

    Fitness Variance of Formae and Performance Prediction

    The Troubling Aspects of a Building Block Hypothesis for Genetic Programming

    Part 2: Convergence and Predictive Models

    Order Statistics for Convergence Velocity Analysis of Simplified Evolutionary Algorithms

    Stability of Vertex Fixed Points and Applications

    Using Markov Chains to Analyze GAFOs

    Predictive Models Using Fitness Distributions of Genetic Operators

    Modeling Simple Genetic Algorithms for Permutation Problems

    Population Size and Genetic Drift in Fitness Sharing

    An Approach to the Study of Sensitivity for a Class of Genetic Algorithms

    Part 3: Fitness Landscapes and Genetic Operators

    Genetic Algorithm Difficulty and the Modality of Fitness Landscapes

    Greedy Recombination and Genetic Search on the Space of Computer Programs

    Productive Recombination and Propagating and Preserving Schemata

    The Role of Development in Genetic Algorithms

    Author Index

    Key Word Index

Product details

  • No. of pages: 300
  • Language: English
  • Copyright: © Morgan Kaufmann 1995
  • Published: March 7, 1994
  • Imprint: Morgan Kaufmann
  • eBook ISBN: 9781483295022

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