Niet blij met je aankoop? Geeft niet! Je kunt artikelen tot 30 dagen retourneren
Met een cadeaubon zit je altijd goed. De ontvanger kan de cadeaubon voor alles uit ons assortiment inwisselen.
Tot 30 dagen retourrecht
This book§introduces numerous algorithmic hybridizations between both worlds that show§how machine learning can improve and support evolution strategies. The set of§methods comprises covariance matrix estimation, meta-modeling of fitness and§constraint functions, dimensionality reduction for search and visualization of§high-dimensional optimization processes, and clustering-based niching. After§giving an introduction to evolution strategies and machine learning, the book§builds the bridge between both worlds with an algorithmic and experimental§perspective. Experiments mostly employ a (1+1)-ES and are implemented in Python§using the machine learning library scikit-learn. The examples are conducted on§typical benchmark problems illustrating algorithmic concepts and their§experimental behavior. The book closes with a discussion of related lines of§research.§
Hoi! Ik ben Libroamiko, je boekadviseur.
Hoe kan ik je helpen?