Artificial Intelligence - General, Genetics - General and Miscellaneous, Evolutionary Computation & Genetic Algorithms, Neural Networks

Genetic Algorithms in Engineering and Computer Science

Name: Genetic Algorithms in Engineering and Computer Science
Author: G. Winter... [et al.]
ISBN: 9780471958598

by G. Winter... [et al.]

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Overview

Genetic Algorithms in Engineering and Computer Science Edited by G. Winter University of Las Palmas, Canary Islands, Spain J. Périaux Dassault Aviation, Saint Cloud, France M. Galán P. Cuesta University of Las Palmas, Canary Islands, Spain This attractive book alerts us to the existence of evolution based software — Genetic Algorithms and Evolution Strategies—used for the study of complex systems and difficult optimization problems unresolved until now. Evolution algorithms are artificial intelligence techniques which mimic nature according to the "survival of the fittest" (Darwin's principle). They randomly encode physical (quantitative or qualitative) variables via digital DNA inside computers and are known for their robustness to better explore large search spaces and find near-global optima than traditional optimization methods. The objectives of this volume are two-fold:

to present a compendium of state-of-the-art lectures delivered by recognized experts in the field on theoretical, numerical and applied aspects of Genetic Algorithms for the computational treatment of continuous, discrete and combinatorial optimization problems.
to provide a bridge between Artificial Intelligence and Scientific Computing in order to increase the performance of evolution programs for solving real life problems.

Fluid dynamics, structure mechanics, electromagnetics, automation control, resource optimization, image processing and economics are the featured multi-disciplinary areas among others in Engineering and Applied Sciences where evolution works impressively well. This volume is aimed at graduate students, applied mathematicians, computerscientists, researchers and engineers who face challenging design optimization problems in Industry. They will enjoy implementing new programs using these evolution techniques which have been experimented with by Nature for 3.5 billion years.

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Booknews

Presents 22 state-of-the-art lectures on an emergent optimization approach based on artificial intelligence coupled with Darwin's rules of evolution. Contributions are intended to provide a bridge between the fields of artificial intelligence and scientific computing in order to increase the performance of evolution programs for solving real-life problems. The main part of the volume discusses the theoretical and computational aspects of genetic algorithms and evolution strategies, while the second section covers applications and computational implementation. Intended for graduate students, applied mathematicians, computer scientists, researchers, and engineers. Lacks a subject index. Annotation c. by Book News, Inc., Portland, Or.