Original title: Towards Low-Dimensional Gaussian Process Metamodels for CMA-ES
Authors: Bajer, Lukáš ; Holeňa, Martin
Document type: Papers
Conference/Event: ITAT 2014. European Conference on Information Technologies - Applications and Theory /14./, Demänovská dolina (SK), 2014-09-25 / 2014-09-29
Year: 2014
Language: eng
Abstract: Gaussian processes and kriging models has attracted attention of researchers from different areas of black-box optimization, especially since Jones’ introduction of the Efficient Global Optimization (EGO) algorithm. However, current implementations of the EGO or real-world applications are rather few. We conjecture that the EGO is not suitable for higher-dimensional optimization and try to investigate whether hybridization of a low-dimensional local optimization with the current state-of-the-art continuous black-box optimizer CMA-ES (Covariance Matrix Adaptation Evolution Strategy) could help. In this paper, only a first proposal of such a GP/CMA-ES connection is described and some preliminary tests are presented.
Keywords: CMA-ES; Gaussian processes; global optimization; metamodel; surrogate model
Project no.: GA13-17187S (CEP)
Funding provider: GA ČR
Host item entry: ITAT 2014. Information Technologies - Applications and Theory. Part II, ISBN 978-80-87136-19-5

Institution: Institute of Computer Science AS ČR (web)
Document availability information: Fulltext is available in the digital repository of the Academy of Sciences.
Original record: http://hdl.handle.net/11104/0236768

Permalink: http://www.nusl.cz/ntk/nusl-175458


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