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GECCO
2009
Springer

AMaLGaM IDEAs in noisy black-box optimization benchmarking

10 years 7 months ago
AMaLGaM IDEAs in noisy black-box optimization benchmarking
This paper describes the application of a Gaussian Estimation-of-Distribution (EDA) for real-valued optimization to the noisy part of a benchmark introduced in 2009 called BBOB (Black-Box Optimization Benchmarking). Specifically, the EDA considered here is the recently introduced parameter-free version of the Adapted Maximum-Likelihood Gaussian Model Iterated Density-Estimation Evolutionary Algorithm (AMaLGaM-IDEA). Also the version with incremental model building (iAMaLGaM-IDEA) is considered. Categories and Subject Descriptors
Peter A. N. Bosman, Jörn Grahl, Dirk Thierens
Added 24 Jul 2010
Updated 24 Jul 2010
Type Conference
Year 2009
Where GECCO
Authors Peter A. N. Bosman, Jörn Grahl, Dirk Thierens
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