Lists (4)
Stars
cognitive-os · 认知操作系统 — 13 Skills + 4 Rules + 4 SubAgents，把人脑分层记忆结构外化为 AI 可操作的知识体系，以50年认知科学研究为基础
🟣 Reinforcement Learning interview questions and answers to help you prepare for your next machine learning and data science interview in 2026.
[Lumina具身智能社区] 具身智能技术指南 Embodied-AI-Guide
Implementation of all RL algorithms in a simpler way
PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..
A clean Pytorch implementation of DDPG on continuous action space.
A curated list of awesome libraries, packages, strategies, books, blogs, tutorials for systematic trading.
PyTorch deep learning projects made easy.
A best practice for deep learning project template architecture.
A Pytorch Computer Vision template to quick start your next project! 🚀🚀
An elegant PyTorch deep reinforcement learning library.
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
Massively Parallel Deep Reinforcement Learning. 🔥
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
Related papers for reinforcement learning, including classic papers and latest papers in top conferences
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Deep Reinforcement Learning: Zero to Hero!
Repository for Open Source Reinforcement Learning Framework JORLDY
PyTorch implementations of deep reinforcement learning algorithms and environments
Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code
📚 List of Top-tier Conference Papers on Reinforcement Learning (RL)，including: NeurIPS, ICML, AAAI, IJCAI, AAMAS, ICLR, ICRA, etc.
Curated list for Deep Reinforcement Learning (DRL): software frameworks, models, datasets, gyms, baselines...
PyTorch implementation of A3C (Asynchronous Advantage Actor Critic)
32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.
A curated list of reinforcement learning with human feedback resources (continually updated)