iBOA: The Incremental Bayesian Optimization Algorithm

dc.creatorPelikan, Martin
dc.creatorSastry, Kumara
dc.creatorGoldberg, David E.
dc.date2008-01-21
dc.date.accessioned2026-07-07T09:53:23Z
dc.date.available2026-07-07T09:53:23Z
dc.descriptionThis 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.
dc.descriptionAlso available at the MEDAL web site, http://medal.cs.umsl.edu/
dc.identifierhttps://arxiv.org/abs/0801.3113
dc.identifierhttp://arxiv.org/abs/0801.3113
dc.identifierProceedings of the Genetic and Evolutionary Computation Conference (GECCO-2008), ACM Press, 455-462
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/165935
dc.subjectNeural and Evolutionary Computing
dc.subjectArtificial Intelligence
dc.subjectI.2.6; I.2.8; G.1.6
dc.titleiBOA: The Incremental Bayesian Optimization Algorithm
dc.typetext

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