Genetic Algorithms: Principles and Perspectives : A Guide to Ga Theory

Colin R Reeves

ISBN 10: 1402072406 / ISBN 13: 9781402072406

Editore: Springer Us Dez 2002, 2002

Riguardo questo articolo

Neuware - 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.

Codice articolo 9781402072406

Dati bibliografici

• Titolo: Genetic Algorithms: Principles and Perspectives : A Guide to Ga Theory
• Editore: Springer Us Dez 2002
• Data di pubblicazione: 2002
• Lingua: Inglese
• ISBN 10: 1402072406
• ISBN 13: 9781402072406
• Rilegatura: Buch
• Condizione: Neu

Descrizione articolo

Riassunto

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.

Contenuti

1. Introduction. 2. Basic Principles. 3. Schema Theory. 4. Non Free Lunch for GAs. 5. GAs as Markov Processes. 6. The Dynamical Systems Model. 7. Statistical Mechanics Approximations. 8. Predicting GA Performance. 9. Landschapes. 10. Summary. A: Test Problems. Bibliography. Index.