2009
AMaLGaM IDEAs in Noiseless Black-Box Optimization Benchmarking
Publication
Publication
Presented at the
Genetic and Evolutionary Computation Conference, Montreal, Canada
This paper describes the application of a Gaussian Estimation-of-Distribution (EDA) for real-valued optimization to the noiseless 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.
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| ACM Press | |
| A. Auger , H.-G. Beyer , N. Hansen , S. Finck , R. Ros , M. Schoenauer , D. Whitley | |
| Genetic and Evolutionary Computation Conference | |
| Organisation | Intelligent and autonomous systems |
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Bosman, P., Grahl, J., & Thierens, D. (2009). AMaLGaM IDEAs in Noiseless Black-Box Optimization Benchmarking. In A. Auger, H.-G. Beyer, N. Hansen, S. Finck, R. Ros, M. Schoenauer, & D. Whitley (Eds.), Proceedings of ACM Annual Genetic and Evolutionary Computation Conference 2009 (pp. 2247–2254). ACM Press. |
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