sweetice/Deep-reinforcement-learning-with-pytorch
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
This project provides pre-built code examples for a range of deep reinforcement learning algorithms. It helps machine learning practitioners, researchers, or students apply various algorithms like DQN, PPO, or SAC to solve control problems in simulated environments. You input an environment description and desired algorithm, and it outputs a trained model capable of performing actions in that environment.
4,589 stars. No commits in the last 6 months.
Use this if you are a machine learning researcher or student who wants to understand and experiment with deep reinforcement learning algorithms using PyTorch.
Not ideal if you are looking for a plug-and-play solution for a specific real-world problem without needing to understand the underlying algorithms or if you are not familiar with Python and PyTorch.
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Mar 24, 2023
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