Multi-Fidelity Multi-Objective Bayesian Optimization: An Output Space Entropy Search Approach

Requirements

The code is implemented in Python and requires the following packages:

1. platypus

2. sklearn.gaussian_process

3. pygmo

Citation

If you use this code in your academic work please cite our papers:

@inproceedings{belakaria2020multifidelity,
  title={Multi-fidelity multi-objective bayesian optimization: an output space entropy search approach},
  author={Belakaria, Syrine and Deshwal, Aryan and Doppa, Janardhan Rao},
  booktitle={Proceedings of the AAAI Conference on artificial intelligence},
  volume={34},
  number={06},
  pages={10035--10043},
  year={2020}
}
@article{belakaria2021output,
  title={Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization},
  author={Belakaria, Syrine and Deshwal, Aryan and Doppa, Janardhan Rao},
  journal={Journal of Artificial Intelligence Research},
  volume={72},
  pages={667-715},
  year={2021}
}