XinJingHao/DRL-Pytorch

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

3436 stars · 389 forks observed · 2026-08-28

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

A unified PyTorch implementation collection of popular deep reinforcement learning algorithms including DQN variants, PPO, DDPG, TD3, SAC, and ASL. Each algorithm lives in its own folder with a main.py training script built on Gymnasium environments.

Use cases

• implement deep reinforcement learning algorithms in pytorch
• learn how PPO works with clean code
• train a DQN agent on gymnasium environments
• compare SAC TD3 and DDPG implementations
• reference implementation for continuous control RL
• study reinforcement learning algorithms from scratch

When to choose

• You want clean, readable reference implementations of classic DRL algorithms
• You are learning or teaching reinforcement learning with PyTorch
• You need a starting codebase to modify for your own RL experiments

When to avoid

• You need a production RL training framework with distributed scaling
• You require a maintained, licensed library with API guarantees
• You want a high-level RL library like Stable-Baselines3 with unified APIs

Facets

library · maturity active

reinforcement-learning machine-learning deep-learning reinforcement-learning machine-learning deep-learning python cross-platform pytorch dqn ppo sac td3 ddpg q-learning gymnasium education gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="XinJingHao/DRL-Pytorch")