This project is a pytorch implementation of Evolutionary Preference Sampling for Pareto Set Learning
Our provide the packages file of our environment (requirement.txt), you can using the following command to download the environment:
- pip install -r requirements.txt
- problem_name: Testing problems. (0: Normal, 1:EPS strategy)
- scalar: Scalarization function (tch2: Tchebycheff function, tch1: Modified Tchebycheff function, cosmos: A Feature fusion method, hv1: hypervolume optimization)
To train a model with GPU run:
- Using EPS strategy:
cd /projects/EPS
python train_net.py --problem_name 'dtlz7' --using_adapt 1
- Do not use EPS strategy:
cd /projects/EPS
python train_net.py --problem_name 'dtlz7' --using_adapt 0
Our paper can be accessed at https://arxiv.org/abs/2404.08414.
@article{ye2024evolutionary, title={Evolutionary Preference Sampling for Pareto Set Learning}, author={Ye, Rongguang and Chen, Longcan and Zhang, Jinyuan and Ishibuchi, Hisao}, journal={arXiv preprint arXiv:2404.08414}, year={2024} }