An Introduction to Genetic Algorithms

by Mitchell, Melanie

• ISBN13: 9780262631853
• ISBN10: 0262631857
• Edition: Reprint
• Format: Paperback
• Copyright: 1998-03-02
• Publisher: Bradford Books
• More Book Details

Summary

Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics -- particularly in machine learning, scientific modeling, and artificial life -- and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithmsis accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.

Author Biography

Melanie Mitchell, Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan, is a Fellow of the Michigan Society of Fellows. She is also Director of the Adaptive Computation Program at the Santa Fe Institute.

Table of Contents

Preface

Acknowledgments

Genetic Algorithms: An Overview

A Brief History of Evolutionary Computation

The Appeal of Evolution

Biological Terminology

Search Spaces and Fitness Landscapes

Elements Of Genetic Algorithms

A Simple Genetic Algorithm

Genetic Algorithms and Traditional Search Methods

Some Applications of Genetic Algorithms

Two Brief Examples

How Do Genetic Algorithms Work?

Genetic Algorithms in Problem Solving

Evolving Computer Programs

Data Analysis and Prediction

Evolving Neural Networks

Genetic Algorithms in Scientific Models

Modeling Interactions Between Learning And Evolution

Modeling Sexual Selection

Modeling Ecosystems

Measuring Evolutionary Activity

Theoretical Foundations of Genetic Algorithms

Schemas and the Two-Armed Bandit Problem

Royal Roads

Exact Mathematical Models Of Simple Genetic Algorithms

Statistical-Mechanics Approaches

Implementing a Genetic Algorithm

When Should a Genetic Algorithm Be Used?

Encoding a Problem for a Genetic Algorithm

Adapting the Encoding

Selection Methods

Genetic Operators

Parameters for Genetic Algorithms

Conclusions and Future Directions

Incorporating Ecological Interactions

Incorporating New Ideas from Genetics

Incorporating Development and Learning

Adapting Encodings and Using Encodings That Permit Hierarchy and Open-Endedness

Adapting Parameters

Connections with the Mathematical Genetics Literature

Extension of Statistical Mechanics Approaches

Identifying and Overcoming Impediments to the Success of GAs

Understanding the Role of Schemas in GAs

Understanding the Role of Crossover

Theory of GAs With Endogenous Fitness

Selected General References

Other Resources

Selected Journals Publishing Work on Genetic Algorithms

Selected Annual or Biannual Conferences Including Work on Genetic Algorithms

Internet Mailing Lists, World Wide Web Sites, and News Groups with Information and Discussions on Ge...

Bibliography

Index

Table of Contents provided by Publisher. All Rights Reserved.