abcdRL (Implement a RL algorithm in four simple steps)

abcdRL is a Modular Single-file RL Algorithms Library🗄 that provides modular🏗 design without strict🚥 and clean single-file📜 implementation.

When reading📖 the code, understand the full implementation details of the algorithm in the single file📜 quickly; When modifying🖌 the algorithm, benefiting from a lightweight🍃 modular design, only need to focus on a small number of modules.

Note

abcdRL mainly references the single-file design philosophy of vwxyzjn/cleanrl and the module design of PaddlePaddle/PARL.

🗽 Design Philosophy

• "Copy📋", not "Inheritance🧬"
• "Single-file📜", not "Multi-file📚"
• "Features reuse🛠", not "Algorithms reuse🖨"
• "Unified logic🤖", not "Unified interface🔌"

✅ Implemented Algorithms

• Deep Q Network (DQN)
• Deep Deterministic Policy Gradient (DDPG)
• Twin Delayed Deep Deterministic Policy Gradient (TD3)
• Soft Actor-Critic (SAC)
• Proximal Policy Optimization (PPO)

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• Double Deep Q Network (DDQN)
• Prioritized Deep Q Network (PDQN)