A Lightweight and Stable DRL Implementation Using PyTorch
ElegantRL ElegantRL is featured with lightweight, efficient and stable, for researchers and practitioners. Lightweight: The core codes <1,000 lines (check elegantrl/tutorial), using PyTorch (train), OpenAI Gym (env), NumPy, Matplotlib (plot). Efficient: performance is comparable with Ray RLlib. Stable: as stable as Stable Baseline 3. Currently, model-free deep reinforcement learning (DRL) algorithms: DDPG, TD3, SAC, A2C, PPO, PPO(GAE) for continuous actions DQN, DoubleDQN, D3QN for discrete actions For DRL algorithms, please check out the educational webpage OpenAI Spinning Up. File Structure […]
Read more