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Genetic Algorithms: Principles and Perspectives - A Guide to GA Theory (Hardcover, 2002 ed.): Colin R. Reeves, Jonathan E Rowe Genetic Algorithms: Principles and Perspectives - A Guide to GA Theory (Hardcover, 2002 ed.)
Colin R. Reeves, Jonathan E Rowe
R4,391 Discovery Miles 43 910 Ships in 10 - 15 working days

Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory is a survey of some important theoretical contributions, many of which have been proposed and developed in the Foundations of Genetic Algorithms series of workshops. However, this theoretical work is still rather fragmented, and the authors believe that it is the right time to provide the field with a systematic presentation of the current state of theory in the form of a set of theoretical perspectives. The authors do this in the interest of providing students and researchers with a balanced foundational survey of some recent research on GAs. The scope of the book includes chapter-length discussions of Basic Principles, Schema Theory, "No Free Lunch," GAs and Markov Processes, Dynamical Systems Model, Statistical Mechanics Approximations, Predicting GA Performance, Landscapes and Test Problems.

Genetic Algorithms: Principles and Perspectives - A Guide to GA Theory (Paperback, Softcover reprint of the original 1st ed.... Genetic Algorithms: Principles and Perspectives - A Guide to GA Theory (Paperback, Softcover reprint of the original 1st ed. 2002)
Colin R. Reeves, Jonathan E Rowe
R3,708 Discovery Miles 37 080 Out of stock

Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory is a survey of some important theoretical contributions, many of which have been proposed and developed in the Foundations of Genetic Algorithms series of workshops. However, this theoretical work is still rather fragmented, and the authors believe that it is the right time to provide the field with a systematic presentation of the current state of theory in the form of a set of theoretical perspectives. The authors do this in the interest of providing students and researchers with a balanced foundational survey of some recent research on GAs. The scope of the book includes chapter-length discussions of Basic Principles, Schema Theory, "No Free Lunch", GAs and Markov Processes, Dynamical Systems Model, Statistical Mechanics Approximations, Predicting GA Performance, Landscapes and Test Problems.

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