Genetic Algorithms—Principles and Perspectives A Guide to GA Theory /

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 t...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Reeves, Colin R. (Συγγραφέας), Rowe, Jonathan E. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Boston, MA : Springer US, 2002.
Σειρά:Operations Research/Computer Science Interfaces Series, 20
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Reeves, Colin R.  |e author. 
245 1 0 |a Genetic Algorithms—Principles and Perspectives  |h [electronic resource] :  |b A Guide to GA Theory /  |c by Colin R. Reeves, Jonathan E. Rowe. 
264 1 |a Boston, MA :  |b Springer US,  |c 2002. 
300 |a XI, 332 p. 4 illus.  |b online resource. 
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490 1 |a Operations Research/Computer Science Interfaces Series,  |x 1387-666X ;  |v 20 
505 0 |a Basic Principles -- Schema Theory -- No Free Lunch for GAs -- GAs as Markov Processes -- The Dynamical Systems Model -- Statistical Mechanics Approximations -- Predicting GA Performance -- Landscapes -- Summary. 
520 |a 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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650 0 |a Artificial intelligence. 
650 0 |a Mathematical optimization. 
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650 2 4 |a Optimization. 
650 2 4 |a Statistics, general. 
650 2 4 |a Operation Research/Decision Theory. 
700 1 |a Rowe, Jonathan E.  |e author. 
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