Introduction to evolutionary computing / A.E. Eiben, J.E. Smith

By: Eiben, Agoston E [author.]Contributor(s): Smith, J. E. (James E.), 1964- [author.] | Ohio Library and Information NetworkMaterial type: TextTextSeries: Natural computing seriesPublisher: Berlin : Springer, 2015Edition: Second edition; Second editionDescription: 1 online resource (xi, 287 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9783662448748; 3662448742Subject(s): Evolutionary programming (Computer science) | Evolutionary computationGenre/Form: Electronic books. DDC classification: 006.3/823 LOC classification: QA76.618Online resources: Click here to access online | Click here to access online | SpringerLink Connect to resource (off-campus)
Contents:
Problems to Be Solved -- Evolutionary Computing: The Origins -- What Is an Evolutionary Algorithm? -- Representation, Mutation, and Recombination -- Fitness, Selection, and Population Management -- Popular Evolutionary Algorithm Variants -- Hybridisation with Other Techniques: Memetic Algorithms -- Nonstationary and Noisy Function Optimisation -- Multiobjective Evolutionary Algorithms -- Constraint Handling -- Interactive Evolutionary Algorithms -- Coevolutionary Systems -- Theory -- Evolutionary Robotics -- Parameters and Parameter Tuning -- Parameter Control -- Working with Evolutionary Algorithms -- References
Summary: 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
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Item type Current library Collection Call number Status Date due Barcode
e-Books e-Books Main Library -University of Zimbabwe
Main Hall Computers
Click on Online resources to access the e-Book QA76.618 (Browse shelf (Opens below)) Available

Includes bibliographical references and index

Problems to Be Solved -- Evolutionary Computing: The Origins -- What Is an Evolutionary Algorithm? -- Representation, Mutation, and Recombination -- Fitness, Selection, and Population Management -- Popular Evolutionary Algorithm Variants -- Hybridisation with Other Techniques: Memetic Algorithms -- Nonstationary and Noisy Function Optimisation -- Multiobjective Evolutionary Algorithms -- Constraint Handling -- Interactive Evolutionary Algorithms -- Coevolutionary Systems -- Theory -- Evolutionary Robotics -- Parameters and Parameter Tuning -- Parameter Control -- Working with Evolutionary Algorithms -- References

Available to OhioLINK libraries

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

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