https://github.com/bstee615/rllab-adv
Code to train RL agents along with Adversarial distrubance agents
Science Score: 10.0%
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Low similarity (6.9%) to scientific vocabulary
Last synced: 10 months ago
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Code to train RL agents along with Adversarial distrubance agents
Basic Info
- Host: GitHub
- Owner: bstee615
- Default Branch: master
- Homepage: https://arxiv.org/abs/1703.02702
- Size: 6.26 MB
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- Watchers: 1
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Fork of lerrel/rllab-adv
Created over 5 years ago
· Last pushed over 9 years ago
https://github.com/bstee615/rllab-adv/blob/master/
>Under Development # Robust Adversarial Reinforcement Learning This repo contains code for training RL agents with adversarial disturbance agents in our work on Robust Adversarial Reinforcement Learning ([RARL](https://arxiv.org/abs/1703.02702)). We build heavily build on the OpenAI rllab repo. ## Installation instructions Since we build upon the [rllab](https://github.com/openai/rllab) package for the optimizers, the installation process is similar to `rllab's` manual installation. Most of the packages are virtually installated in the anaconda `rllab3-adv` enivronment. - Dependencies for scipy: ``` sudo apt-get build-dep python-scipy ``` - Install python modules: ``` conda env create -f environment.yml ``` - [Install MuJoCo](https://github.com/openai/mujoco-py) - Add `rllab-adv` to your `PYTHONPATH`. ``` export PYTHONPATH=:$PYTHONPATH ``` ## Example ```python # Enter the anaconda virtual environment source activate rllab3-adv # Train on InvertedPendulum python adversarial/scripts/train_adversary.py --env InvertedPendulumAdv-v1 --folder ~/rllab-adv/results ``` ## Contact Lerrel Pinto -- lerrelpATcsDOTcmuDOTedu.
Owner
- Name: Benjamin Steenhoek
- Login: bstee615
- Kind: user
- Website: benjijang.com
- Repositories: 12
- Profile: https://github.com/bstee615
3rd year PhD student @ ISU. Interests and research: deep learning, program analysis