adaptive systems theory
advanced evolutionary algorithm applications
Allele Value
artificial evolution methods
Binary Strings
Boltzmann Selection
Canonical Genetic Algorithms
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Category=UB
computational intelligence
Crossover Operator
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Evolutionary Algorithms
Evolutionary Computation
Finite State Machines
Fitness Function
Generational Evolutionary Algorithm
Genetic Algorithms
Genetic Operators
Linear Rank Selection
Linear Ranking
Local Search Operator
machine learning foundations
Membership Function
Mutation Operators
Objective Function
optimisation techniques
Output Symbol
Parse Tree
Parse Tree Representations
Recombination Operators
search heuristics
Strategy Parameters
Tournament Selection
Traveling Salesman Problem
Product details
- ISBN 9781138413085
- Weight: 662g
- Dimensions: 156 x 234mm
- Publication Date: 27 Jul 2017
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
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The field of evolutionary computation is expanding dramatically, fueled by the vast investment that reflects the value of applying its techniques. Culling material from the Handbook of Evolutionary Computation, Evolutionary Computation 1: Basic Algorithms and Operators contains up-to-date information on algorithms and operators used in evolutionary computing. This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming. It is intended to be used by individual researchers, teachers, and students working and studying in this expanding field.
Thomas Baeck, D.B Fogel, Z Michalewicz
