Comparison of Low-budget Black-box Optimization Algorithms on BBOB

Data to replicate the results presented in the paper "Low-budget Black-box Optimization Algorithms in BBOB and OpenAI Gym", submitted to IEEE Transactions on Evolutionary Computation. Here, we offer the data comparing Black-Box Optimization tools for machine learning with more classical heuristics on the well-known BBOB benchmark suite from the COCO environment (24 noiseless functions with different landscape characteristics: uni/multi-modality, separability, good/weak global structure, etc.)

Related Organizations

French National Centre for Scientific Research
France
Leiden University
Netherlands
Sorbonne Université
France
University of Antananarivo
Madagascar

Keywords

Benchmarking, Black-box optimization, BBOB, Bayesian Optimization.

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