Open Access
Hierarchical Bayesian Optimization Algorithm.
Martin Pelikan,David E. Goldberg +1 more
- 01 Jan 2006
pp 63-90
179
TL;DR: The hierarchical Bayesian optimization algorithm (hBOA) as discussed by the authors solves nearly decomposable and hierarchical optimization problems scalably by combining concepts from evolutionary computation, machine learning and statistics.
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Abstract: The hierarchical Bayesian optimization algorithm (hBOA) solves nearly decomposable and hierarchical optimization problems scalably by combining concepts from evolutionary computation, machine learning and statistics. Since many complex real-world systems are nearly decomposable and hierarchical, hBOA is expected to provide scalable solutions for many complex real-world problems. This chapter describes hBOA and its predecessor, the Bayesian optimization algorithm (BOA), and outlines some of the most important theoretical and empirical results in this line of research.
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