This is the EECS 598 - 002 RL course project for the PyTorch implementation for OML-PPO (https://iopscience.iop.org/article/10.1088/2632-2153/abc327) without spinningup
- python=3.7.4
- torch=1.3.1
- torchvision=0.5.0
- tmm=0.1.7
- make environment: conda create --name py37 python=3.7
- make RLMultilayer package: pip install -e .
- Install any necessary packages.
Max length = 6:
python ppo_absorber_visnir.py --cpu 16 --maxlen 6 --exp_name absorber6 --use_rnn --discrete_thick --num_runs 1 --env PerfectAbsorberVisNIR-v0
Max length = 15:
python ppo_absorber_visnir.py --cpu 16 --maxlen 15 --exp_name perfect_absorber15 --use_rnn --discrete_thick --num_runs 1 --env PerfectAbsorberVisNIR-v1
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- Add perturbation to thickness
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- Add extra rewards at middle steps