Reactive Search and Intelligent Optimization

Roberto Battiti

ISBN 10: 038709623X / ISBN 13: 9780387096230

Edité par Springer Us, 2008

A propos de cet article

Druck auf Anfrage Neuware - Printed after ordering - Reactive Search and Intelligent Optimization is an excellent introduction to the main principles of reactive search, as well as an attempt to develop some fresh intuition for the approaches. The book looks at different optimization possibilities with an emphasis on opportunities for learning and self-tuning strategies. While focusing more on methods than on problems, problems are introduced wherever they help make the discussion more concrete, or when a specific problem has been widely studied by reactive search and intelligent optimization heuristics.Individual chapters cover reacting on the neighborhood; reacting on the annealing schedule; reactive prohibitions; model-based search; reacting on the objective function; relationships between reactive search and reinforcement learning; and much more. Each chapter is structured to show basic issues and algorithms; the parameters critical for the success of the different methods discussed; and opportunities forthe automated tuning of these parameters.

N° de réf. du vendeur 9780387096230

Détails bibliographiques

• Titre: Reactive Search and Intelligent Optimization
• Éditeur: Springer Us
• Date de parution: 2008
• Langue: anglais
• ISBN à 10 chiffres: 038709623X
• ISBN à 13 chiffres: 9780387096230
• Reliure: Buch
• État de l'article: Neu
• Dimensions: 244 L x 161 H x 16 P (en millimètres) 244 millimètres de largeur par 161 millimètres de hauteur par 16 millimètres de profondeur
• Poids: 426 grammes

A propos de ce titre

Synopsis

Reactive Search and Intelligent Optimization is an excellent introduction to the main principles of reactive search, as well as an attempt to develop some fresh intuition for the approaches. The book looks at different optimization possibilities with an emphasis on opportunities for learning and self-tuning strategies. While focusing more on methods than on problems, problems are introduced wherever they help make the discussion more concrete, or when a specific problem has been widely studied by reactive search and intelligent optimization heuristics.

Individual chapters cover reacting on the neighborhood; reacting on the annealing schedule; reactive prohibitions; model-based search; reacting on the objective function; relationships between reactive search and reinforcement learning; and much more. Each chapter is structured to show basic issues and algorithms; the parameters critical for the success of the different methods discussed; and opportunities forthe automated tuning of these parameters.