Config files for my GitHub profile.

Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

Sparrow-V2: A Reinforcement Learning Friendly Mobile Robot Simulator for Dynamic Environments

OkayPlan: A real-time global path palnning algorithm for dynamic environments

A Reinforcement Learning Friendly Simulator for Mobile Robot

a clean and robust Pytorch implementation of SAC on continuous action space

A Reinforcement Learning Friendly Simulator for Multiple Mobile Robot

The author's implementation of the OPCD (OkayPlan-ColorDynamic) navigation system.

ColorDynamic: Generalizable, Scalable, Real-time, End-to-end Local Planner for Unstructured and Dynamic Environments

Hold repostories' images

A Reinforcement Learning Friendly Simulator for Mobile Robot

Real-time global path planning algorithm for dynamic environments

Actor-Sharer-Learner training framework for off-policy DRL algorithms

Color: Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity

A clean and robust Pytorch implementation of SAC on discrete action space

A clean and robust Pytorch implementation of TD3 on continuous action space

A clean Pytorch implementation of DDPG on continuous action space.

A clean and robust Pytorch implementation of PPO on continuous action space.

A clean and robust Pytorch implementation of PPO on Discrete action space

A clean and robust implementation of NoisyNet DQN

A clean and robust Pytorch implementation of Categorical DQN (C51)

A clean and robust implementation of Prioritized DQN and Prioritized Double DQN

A clean and robust implementation of Noisy-Duel-DDQN on Atari games

A clean and robust implementation of Duel Double DQN

Efficient Real-time Path Planning with SEPSO in Dynamic Scenarios

An implementation of Q-learning

Solve BipedalWalkerHardcore-v2 with TD3