TianhongDai/reinforcement-learning-algorithms
This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are still in progress)
This project helps machine learning engineers and researchers implement classic deep reinforcement learning algorithms using PyTorch. It provides clear, modular code for various algorithms like DQN, DDPG, and PPO, allowing users to train agents on environments such as Atari games or robotic simulations. The output is a trained agent capable of performing tasks within a simulated environment.
693 stars.
Use this if you are a machine learning practitioner looking for a clear, PyTorch-based implementation to learn, experiment with, or apply foundational deep reinforcement learning algorithms.
Not ideal if you need a plug-and-play solution for a specific real-world problem without needing to understand or modify the underlying reinforcement learning algorithms.
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693
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110
Language
Python
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Last pushed
Dec 18, 2025
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