zenodoopen
Comparison of Low-budget Black-box Optimization Algorithms on BBOB
<p>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.)</p>
ShareScore
28/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 0
- Engagement
- 0