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...
Zapisane w:
| Główni autorzy: | , , |
|---|---|
| Format: | Livre numérique |
| Język: | Anglais |
| Wydane: |
New York, NY :
Springer US
2009.
Cham : Springer Nature |
| Seria: | Operations Research/Computer Science Interfaces Series
45 |
| Hasła przedmiotowe: | |
| Dostęp online: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Komentarz: |
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 |
Spis treści:
- Introduction: Machine Learning for Intelligent Optimization
- Reacting on the neighborhood
- Reacting on the Annealing Schedule
- Reactive Prohibitions
- Reacting on the Objective Function
- Reacting on the Objective Function
- Supervised Learning
- Reinforcement Learning
- Algorithm Portfolios and Restart Strategies
- Racing
- Teams of Interacting Solvers
- Metrics, Landscapes and Features
- Open Problems.