A Utile Function Optimizer

We recast the problem of unconstrained continuous evolutionary optimization as inference in a fixed graphical model. This approach allows us to address several pervasive issues in optimization, including the traditionally difficult problem of selecting an algorithm that is most appropriate for a giv...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Monson, C.K., Seppi, K.D., Carroll, J.L.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Bayesian methods Computer science Cost function Decision theory Evolutionary computation Graphical models Inference algorithms Navigation Sampling methods Uncertainty
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