ShangtongZhang/DeepRL

Health v2 · maintenance only

Adoption not part of the score

3448 stars · 697 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A modularized PyTorch implementation of popular deep reinforcement learning algorithms including DQN variants, PPO, DDPG, TD3, A2C, and Option-Critic. It supports switching between toy tasks and Atari/Mujoco benchmark environments.

Use cases

• implement deep reinforcement learning algorithms in pytorch
• train a DQN agent on Atari games
• run PPO on Mujoco continuous control tasks
• study reference implementations of Rainbow-style DQN variants
• benchmark deep RL algorithms on a single GPU

When to choose

• you want readable, modular PyTorch code for classic deep RL algorithms
• you need a research baseline implementation of DQN, PPO, DDPG, or TD3
• you want to reproduce paper results on Atari or Mujoco

When to avoid

• you need a production RL training platform with distributed scaling
• you want the latest maintained framework with broad environment support
• you need algorithms beyond the implemented set or newer PyTorch versions

Facets

library · maturity maintenance

machine-learning reinforcement-learning deep-learning reinforcement-learning machine-learning deep-learning python pytorch dqn ppo ddpg td3 a2c option-critic atari mujoco research-code gpu docker

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For agents

markdown · JSON · MCP: product_card(name="ShangtongZhang/DeepRL")