Hierarchical Bayesian Optimization Algorithm : Toward a New Generation of Evolutionary Algorithms
Overview
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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Details
- ISBN-13: 9783540237747
- ISBN-10: 3540237747
- Publisher: Springer
- Publish Date: February 2005
- Dimensions: 9.21 x 6.14 x 0.5 inches
- Shipping Weight: 0.97 pounds
- Page Count: 166
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