Crux

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:

Reinforcement Learning

• Deep Q-Learning (DQN)
  • Prioritized Experience Replay
• Soft Q-Learning
• REINFORCE
• Proximal Policy Optimization (PPO)
• Lagrange-Constrained PPO
• Advantage Actor Critic (A2C)
• Deep Deterministic Policy Gradient (DDPG)
• Twin Delayed DDPG (TD3)
• Soft Actor Critic (SAC)

Imitation Learning

• Behavioral Cloning
• Generative Adversarial Imitation Learning (GAIL) w/ On-Policy and Off-Policy Versions
• Adversarial Value Moment Imitation Learning (AdVIL)
• Adversarial Reward-moment Imitation Learning (AdRIL)
• Soft Q Imitation Learning (SQIL)
• Adversarial Soft Advantage Fitting (ASAF)
• Inverse Q-Learning (IQLearn)

Batch RL

• Batch Soft Actor Critic (BatchSAC)
• Conservative Q-Learning (CQL)

Adversarial RL

• Robust Adversarial RL (RARL)

Continual Learning

• Experience Replay

Citation

In progress.