Reactive search and intelligent optimization
Reactive Search integrates sub-symbolic machine learning techniques into search heuristics for solving complex optimization problems. By automatically adjusting the working parameters, a reactive search self-tunes and adapts, effectively learning by doing until a solution is found. Intelligent Optim...
Αποθηκεύτηκε σε:
| Κύριοι συγγραφείς: | , , |
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| Μορφή: | Livre numérique |
| Γλώσσα: | Anglais |
| Έκδοση: |
New York, NY :
Springer US
2009.
Cham : Springer Nature |
| Σειρά: | Operations Research/Computer Science Interfaces Series
45 |
| Θέματα: | |
| Διαθέσιμο Online: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Σημείωση: |
L'accès complet au document est réservé aux usagers des établissements qui en ont fait l'acquisition Numérisation de l'édition imprimée de New York : Springer, cop. 2008 Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Reactive Search and Intelligent Optimization, Texte imprimé, 9781441934994 • Reactive Search and Intelligent Optimization, Texte imprimé, 9780387561097 • Point defects in metals, II, dynamical properties and diffusion controlled reactions, contributions by P. H. Dederichs, K. Schroeder, R. Zeller, Berlin, Springer-Verlag, 1980, 1 vol. (X-262 p.), Springer tracts in modern physics, 3-540-09623-X |
| Περίληψη: | Reactive Search integrates sub-symbolic machine learning techniques into search heuristics for solving complex optimization problems. By automatically adjusting the working parameters, a reactive search self-tunes and adapts, effectively learning by doing until a solution is found. Intelligent Optimization, a superset of Reactive Search, concerns online and off-line schemes based on the use of memory, adaptation, incremental development of models, experimental algorithms applied to optimization, intelligent tuning and design of heuristics. 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 and schemes for the automated tuning of these parameters. Anyone working in decision making in business, engineering, economics or science will find a wealth of information here. . |
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| Περιγραφή τεκμηρίου: | L'accès complet au document est réservé aux usagers des établissements qui en ont fait l'acquisition Numérisation de l'édition imprimée de New York : Springer, cop. 2008 Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| ISBN: | 0387096248 (en ligne) 9780387096247 (en ligne) |
| ISSN: | 2698-5489 |
| Πρόσβαση: | Accès en ligne pour les établissements français bénéficiaires des licences nationales Accès soumis à abonnement pour tout autre établissement Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |