Reactive Search and Intelligent Optimization

• Κύριοι συγγραφείς: Battiti, Roberto (Συγγραφέας), Brunato, Mauro (Συγγραφέας), Mascia, Franco (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Boston, MA : Springer US, 2009.
• Σειρά: Operations Research/Computer Science Interfaces Series, 45
• Θέματα: Mathematics.; Operations research.; Decision making.; Computers.; Artificial intelligence.; Management science.; Applied mathematics.; Engineering mathematics.; Industrial engineering.; Production engineering.; Operations Research, Management Science.; Operation Research/Decision Theory.; Computing Methodologies.; Artificial Intelligence (incl. Robotics).; Appl.Mathematics/Computational Methods of Engineering.; Industrial and Production Engineering.

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...

Πίνακας περιεχομένων:

• 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.