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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms

Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms

Pelikan, Martin

Paperback

Series: Studies in Fuzziness and Soft Computing, Book 170

General ComputersGeneral MathematicsProgramming

ISBN10: 3642062733
ISBN13: 9783642062735
Publisher: Springer Nature
Published: Oct 21 2010
Pages: 166
Weight: 0.59
Height: 0.40 Width: 6.14 Depth: 9.21
Language: English

This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The primary focus of the book is on two algorithms that replace traditional variation operators of evolutionary algorithms, by learning and sampling Bayesian networks: the Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA). They provide a scalable solution to a broad class of problems. The book provides an overview of evolutionary algorithms that use probabilistic models to guide their search, motivates and describes BOA and hBOA in a way accessible to a wide audience, and presents numerous results confirming that they are revolutionary approaches to black-box optimization.

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