Evolutionary Algorithms Theory Practice by Back Thomas (19 results)

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Hardcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 68 BAE 9780195099713 Sprache: Englisch Gewicht in…Gramm: 1150.

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Condition: New. Compares three prominent representatives of evolutionary algorithms - genetic algorithms, evolution strategies and evolutionary programming - computational methods at the border between computer science and evolutionary biology. The algorithms are explained within a common framework, thereby clarifying the simila…rities and differences. Num Pages: 328 pages, line figures, tables. BIC Classification: PSAJ; UM; UYA. Category: (U) Tertiary Education (US: College). Dimension: 241 x 163 x 23. Weight in Grams: 632. . 1996. Hardback. . . . . Books ship from the US and Ireland.

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Condition: New. Compares three prominent representatives of evolutionary algorithms - genetic algorithms, evolution strategies and evolutionary programming - computational methods at the border between computer science and evolutionary biology. The algorithms are explained within a common framework, thereby clarifying the simila…rities and differences. Num Pages: 328 pages, line figures, tables. BIC Classification: PSAJ; UM; UYA. Category: (U) Tertiary Education (US: College). Dimension: 241 x 163 x 23. Weight in Grams: 632. . 1996. Hardback. . . . .

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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents a unified view of evolutionaryalgorithms: the exciting new probabilistic search toolsinspired by biological models that have immense potential aspractical problem-solvers in a wide variety of settingsacademic, commercial, and… industrial. In this work, theauthor compares the three most prominent representatives ofevolutionary algorithms: genetic algorithms, evolutionstrategies, and evolutionary programming. The algorithms arepresented within a unified framework, thereby clarifying thesimilarities and differences of these methods. The authoralso presents new results regarding the role of mutation andselection in genetic algorithms, showing how mutation seemsto be much more important for the performance of geneticalgorithms than usually assumed. The interaction ofselection and mutation, and the impact of the binary codeare further topics of interest. Some of the theoreticalresults are also confirmed by performing an experiment inmeta-evolution on a parallel computer. The meta-algorithmstrategies and genetic algorithms to yield a hybrid capableof handling mixed integer optimization problems. As adetailed description of the algorithms, with practicalguidelines for usage and implementation, this work willinterest a wide range of researchers in computer science andengineering disciplines, as well as graduate students inthese fields.

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Condition: New. Print on Demand pp. 332.

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Condition: New. Print on Demand pp. 332 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.

- Hardcover
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Condition: New. PRINT ON DEMAND pp. 332.