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)

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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.

reinforcement-learning deep-learning agent-training algorithm-prototyping robotics-simulation
No License No Package No Dependents
Maintenance 6 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 22 / 25

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Stars

693

Forks

110

Language

Python

License

Last pushed

Dec 18, 2025

Commits (30d)

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