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2008
Springer

iBOA: the incremental bayesian optimization algorithm

9 years 1 months ago
iBOA: the incremental bayesian optimization algorithm
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. Categories and Subject Descriptors I.2.6 [Artificial Intelligence]: Learning; I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and
Martin Pelikan, Kumara Sastry, David E. Goldberg
Added 09 Nov 2010
Updated 09 Nov 2010
Type Conference
Year 2008
Where GECCO
Authors Martin Pelikan, Kumara Sastry, David E. Goldberg
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