RL
DRLib：a Concise Deep Reinforcement Learning Library, Integrating HER, PER and D2SR for Almost Off-Policy RL Algorithms.
Simple and easily configurable grid world environments for reinforcement learning
RL starter files in order to immediately train, visualize and evaluate an agent without writing any line of code
Code for hierarchical imitation learning and reinforcement learning
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKT…
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accel 8754 erating ML workloads.
Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.
Clean PyTorch implementations of imitation and reward learning algorithms
Repository to store conditional imitation learning based AI that runs on CARLA.
(CoRL 2019) Driving in CARLA using waypoint prediction and two-stage imitation learning
Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
Implement reinforcement learning algorithms in Pytorch