Evolutionary Computing is the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. These techniques are being increasingly widely applied to a variety of problems, ranging from practical applications
Introduction to Evolutionary Computing
โ Scribed by A.E. Eiben, J.E. Smith (auth.)
- Publisher
- Springer-Verlag Berlin Heidelberg
- Year
- 2015
- Tongue
- English
- Leaves
- 294
- Series
- Natural Computing Series
- Edition
- 2
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
The overall structure of this new edition is three-tier: Part I presents the basics, Part II is concerned with methodological issues, and Part III discusses advanced topics. In the second edition the authors have reorganized the material to focus on problems, how to represent them, and then how to choose and design algorithms for different representations. They also added a chapter on problems, reflecting the overall book focus on problem-solvers, a chapter on parameter tuning, which they combined with the parameter control and "how-to" chapters into a methodological part, and finally a chapter on evolutionary robotics with an outlook on possible exciting developments in this field.
The book is suitable for undergraduate and graduate courses in artificial intelligence and computational intelligence, and for self-study by practitioners and researchers engaged with all aspects of bioinspired design and optimization.
โฆ Table of Contents
Front Matter....Pages I-XII
Front Matter....Pages 1-1
Problems to Be Solved....Pages 1-12
Evolutionary Computing: The Origins....Pages 13-24
What Is an Evolutionary Algorithm?....Pages 25-48
Representation, Mutation, and Recombination....Pages 49-78
Fitness, Selection, and Population Management....Pages 79-98
Popular Evolutionary Algorithm Variants....Pages 99-116
Front Matter....Pages 117-117
Parameters and Parameter Tuning....Pages 119-129
Parameter Control....Pages 131-146
Working with Evolutionary Algorithms....Pages 147-163
Front Matter....Pages 165-165
Hybridisation with Other Techniques: Memetic Algorithms....Pages 167-183
Nonstationary and Noisy Function Optimisation....Pages 185-194
Multiobjective Evolutionary Algorithms....Pages 195-202
Constraint Handling....Pages 203-213
Interactive Evolutionary Algorithms....Pages 215-222
Coevolutionary Systems....Pages 223-229
Theory....Pages 231-244
Evolutionary Robotics....Pages 245-258
Back Matter....Pages 259-287
โฆ Subjects
Artificial Intelligence (incl. Robotics); Computational Intelligence; Theory of Computation; Robotics and Automation; Optimization
๐ SIMILAR VOLUMES
<p><P>Evolutionary Computing is the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. These techniques are being increasingly widely applied to a variety of problems, ranging from practical applic
The overall structure of this new edition is three-tier: Part I presents the basics, Part II is concerned with methodological issues, and Part III discusses advanced topics. In the second edition the authors have reorganized the material to focus on problems, how to represent them, and then how to c
Evolutionary Computing is the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. These techniques are being increasingly widely applied to a variety of problems, ranging from practical applications
Evolutionary Computing is the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. These techniques are being increasingly widely applied to a variety of problems, ranging from practical applications