ppo

hands-on-modern-rl

+51

🚀 An open-source, hands-on curriculum bridging the gap from basic RL concepts to LLM alignment, RLVR, and advanced Agentic systems.

easy-rl

+20

强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/

FinRL-Trading

+26

FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading

FirstLight_CR

+17

Offline Clash Royale AI agent research: native simulation, imitation learning, PPO, and interactive evaluation. 离线对局模拟、模仿学习、强化学习与交互评测。

ZHYsfl/ai-whys

+4

深度学习与强化学习的系统学习路线：39 个实验，每个配数学推导笔记、原创插图和从零实现的代码

minimind-deep-dive

+2

从 MiniMind 源码读起,再延伸到现代大模型技术体系的中文学习笔记。主线逐行精读预训练 / SFT / DPO / PPO / GRPO 与训练机制;附录 17 篇进阶卷覆盖量化、投机解码、RLHF 全景、模型代际史等 MiniMind 没涉及、但进阶绕不开的主题。

kengz/SLM-Lab

+2

Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".

xuance

+1

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library