Deep RL library with concise implementations of popular algorithms. Implemented using Flux.jl and fits into the POMDPs.jl interface.
Supports CPU and GPU computation and implements the following algorithms:
- Deep Q-Learning
- Prioritized Experience Replay
- Soft Q-Learning
- REINFORCE
- Proximal Policy Optimization (PPO)
- Lagrange-Constrained PPO
- Advantage Actor Critic
- Deep Deterministic Policy Gradient (DDPG)
- Twin Delayed DDPG (TD3)
- Soft Actor Critic (SAC)
- Behavioral Cloning
- Generative Adversarial Imitation Learning (GAIL) w/ On-Policy and Off Policy Versions
- Adversarial value moment imitation learning (AdVIL)
- (AdRIL)
- (SQIL)
- Adversarial Soft Advantage Fitting (ASAF)
- Inverse Q-Learning (IQLearn)
- Experience Replay
- Install POMDPGym
- Install by opening julia and running
] add Crux
To edit or contribute use ] dev Crux
and the repo will be cloned to ~/.julia/dev/Crux
Maintained by Anthony Corso (acorso@stanford.edu)