iBOA: The Incremental Bayesian Optimization Algorithm

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Information about iBOA: The Incremental Bayesian Optimization Algorithm

Published on July 18, 2008

Author: pelikan

Source: slideshare.net

Description

This paper proposes the incremental Bayesian optimization algorithm (iBOA), which modifies standard BOA by removing the population of solutions and using incremental updates of the Bayesian network. iBOA is shown to be able to learn and exploit unrestricted Bayesian networks using incremental techniques for updating both the structure as well as the parameters of the probabilistic model. This represents an important step toward the design of competent incremental estimation of distribution algorithms that can solve difficult nearly decomposable problems scalably and reliably.

iBOA Incremental Bayesian Optimization Algorithm Martin Pelikan, Kumara Sastry and David E. Goldberg Missouri Estimation of Distribution Algorithms Laboratory (MEDAL) University of Missouri, St. Louis, MO http://medal.cs.umsl.edu/ pelikan@cs.umsl.edu Illinois Genetic Algorithms Laboratory University of Illinois at Urbana-Champaign, Urbana, IL http://www-illigal.ge.uiuc.edu/ kumara@kumarasastry.com deg@uiuc.edu Martin Pelikan, Kumara Sastry, David E. Goldberg iBOA: The Incremental Bayesian Optimization Algorithm

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