Buch, Englisch, 420 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 743 g
Buch, Englisch, 420 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 743 g
Reihe: International Series on Computational Intelligence
ISBN: 978-0-8493-0588-7
Verlag: Taylor & Francis
Rapid advances in evolutionary computation have opened up a world of applications-a world rapidly growing and evolving. Decision making, neural networks, pattern recognition, complex optimization/search tasks, scheduling, control, automated programming, and cellular automata applications all rely on evolutionary computation.
Evolutionary Computation presents the basic principles of evolutionary computing: genetic algorithms, evolution strategies, evolutionary programming, genetic programming, learning classifier systems, population models, and applications. It includes detailed coverage of binary and real encoding, including selection, crossover, and mutation, and discusses the (m+l) and (m,l) evolution strategy principles. The focus then shifts to applications: decision strategy selection, training and design of neural networks, several approaches to pattern recognition, cellular automata, applications of genetic programming, and more.
Zielgruppe
Professional
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Principles of Evolutionary Computation
Genetic Algorithms
Basic Selection Schemes in Evolutionary Algorithms
Selection Based on Scaling and Ranking Mechanisms
Further Selection Strategies
Recombination Operators within Binary Encoding
Mutation and other Search Operators
Schema Theorem, Building Blocks and Related Topics
Real-valued Encoding
Hybridization, Parameter Setting and Adaptation
Adaptive Representations: Messy Genetic Algorithms, Delta Coding and Diploidic Representation
Evolution Strategies and Evolutionary Programming
Population Models and Parallel Implementations
Genetic Programming
Learning Classifier Systems
Applications of Evolutionary Computation
