The mathematics employed by genetic algorithms (GAs)are among the most exciting discoveries of the last few decades. But what exactly is a genetic algorithm? A genetic algorithm is a problem-solving method that uses genetics as its model of problem solving. It applies the rules of reproduction, gene crossover, and mutation to pseudo-organism

chapter Chapter A|26 pages

Multi-Niche Crowding for Multi-Modal Search

ByV. Rao Vemuri, Walter Cedeño

chapter Chapter 1|22 pages

Artificial Neural Network Evolution: Learning to Steer a Land Vehicle

ByShumeet Baluja

chapter Chapter 2|14 pages

Locating Putative Protein Signal Sequences

Edited ByMichael Levin

chapter Chapter 3|26 pages

Selection Methods for Evolutionary Algorithms

Edited ByPeter J.B. Hancock

chapter Chapter 4|18 pages

Parallel Cooperating Genetic Algorithms: An Application to Robot Motion Planning

Edited ByEl-Ghazali Talbi, Pierre Bessiere, Juan-Manuel Ahuactzin, Emmanuel Mazer

chapter Chapter 5|28 pages

The Boltzmann Selection Procedure 1

ByMichael de la Maza

chapter Chapter 6|16 pages

Structure and Performance of Fine-Grain Parallelism in Genetic Search

Edited ByShumeet Baluja

chapter Chapter 7|18 pages

Parameter Estimation for a Generalized Parallel Loop Scheduling Algorithm

Edited ByKelvin K. Yue, David J. Lilja

chapter Chapter 8|24 pages

Controlling a Dynamic Physical System Using Genetic-Based Learning Methods

ByM. O. Odetayo, D. Dasgupta

chapter Chapter 10|32 pages

Chemical Engineering

Edited ByVijaykumar Hanagandi, Michael Nikolaou

chapter Chapter 11|26 pages

Vehicle Routin1 with Time Windows usin1 Genetic Algorithms

BySam R. Thangiah

chapter Chapter 12|24 pages

Evolutionary Algorithms and Dialogue

Edited ByD.J. Nettleton, R. Garigliano

chapter Chapter 14|16 pages

Input Space Segmentation with a Genetic Algorithm for Generation of Rule Based Classifier Systems

Edited BySaman K. Halgamuge, Manfred Glesner