Proceedings of the First International Conference on Genetic Algorithms and their Applications / Edition 1

by John J. Grefenstette

Overview

Computer solutions to many difficult problems in science and engineering require the use of automatic search methods that consider a large number of possible solutions to the given problems. This book describes recent advances in the theory and practice of one such search method, called Genetic Algorithms. Genetic algorithms are evolutionary search techniques based on principles derived from natural population genetics, and are currently being applied to a variety of difficult problems in science, engineering, and artificial intelligence.

Product Details

ISBN-13:	9781138414204
Publisher:	Taylor & Francis
Publication date:	07/11/2017
Pages:	234
Product dimensions:	8.25(w) x 11.00(h) x (d)
Lexile:	1340L (what's this?)

Table of Contents

Contents: J.H. Holland, Properties of the Bucket Brigade. D.E. Goldberg, Genetic Algorithms and Rules Learning in Dynamic System Control. S.W. Wilson, Knowledge Growth in an Artificial Animal. S. Forrest, Implementing Semantic Network Structures Using the Classifier System. T.H. Westerdale, The Bucket Brigade is Not Genetic. L.A. Rendell, Genetic Plans and the Probabilistic Learning System: Synthesis and Results. J.D. Schaffer, Learning Multiclass Pattern Discrimination. L.B. Booker, Improving the Performance of Genetic Algorithms in Classifier Systems. J.D. Schaffer, Multiple Objective Optimization With Vector Evaluated Genetic Algorithms. J.E. Baker, Adaptive Selection Methods for Genetic Algorithms. J.J. Grefenstette, J.M. Fitzpatrick, Genetic Search With Approximate Function Evaluation. D.H. Ackley, A Connectionist Algorithm for Genetic Search. L. Davis, Job Shop Scheduling With Genetic Algorithms. M.P. Fourman, Compaction of Symbolic Layout Using Genetic Algorithms. D.E. Goldberg, R. Lingle, Jr., Alleles, Loci, and the Traveling Salesman Problem. J.J. Grefenstette, R. Gopal, B.J. Rosmaita, D. Van Gucht, Genetic Algorithms for the Traveling Salesman Problem. K.A. De Jong, Genetic Algorithms: A 10 Year Perspective. H. Zhou, Classifier Systems With Long Term Memory. N.L. Cramer, A Representation for the Adaptive Generation of Simple Sequential Programs. S.W. Wilson, Adaptive ‘Cortical' Pattern Recognition. A.C. Englander, Machine Learning of Visual Recognition Using Genetic Algorithms. D. Smith, Bin Packing With Adaptive Search. C.G. Shaefer, Directed Trees Method for Fitting a Potential Function.