Beschreibung
InhaltsangabeIntroduction: 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.
Inhaltsverzeichnis
Preface.- Introduction.- Reacting on the neighborhood.- Reacting on the annealing schedule.- Reactive prohibitions.- Model-based search.- Reacting on the objective function.- Reinforcement learning.- Algorithm portfolios and restart strategies.- Racing.- Metrics, landscapes, and features.- Relationships between reactive search and reinforcement learning.- Index.