Stars
Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞
Kode Agent — Design for post-human workflows. One unit agent for every human & computer task.
Bash is all you need - A nano claude code–like 「agent harness」, built from 0 to 1
[ACM MM 2025] FantasyTalking: Realistic Talking Portrait Generation via Coherent Motion Synthesis
RLinf: Reinforcement Learning Infrastructure for Embodied and Agentic AI
Vision–Language–Action models for Autonomous Driving (VLA4AD) resources, serving as the companion repository to the survey paper “A Survey on Vision–Language–Action Models for Autonomous Driving”.
[RSS 2025] "ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills"
[ICLR 2025] Cross-Embodiment Dexterous Grasping with Reinforcement Learning
FinRL®: Financial Reinforcement Learning. 🔥
Minimal PyTorch Implementation of PPO for SEED RL
[NeurIPS 2023 Spotlight] LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios (awesome MCTS)
A library of reinforcement learning components and agents
A simple and well styled PPO implementation. Based on my Medium series: https://medium.com/@eyyu/coding-ppo-from-scratch-with-pytorch-part-1-4-613dfc1b14c8.
An Open-source RL System from ByteDance Seed and Tsinghua AIR
An artificial intelligence platform for the StarCraft II with large-scale distributed training and grand-master agents.
A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)
Source Code
Open-source simulator for autonomous driving research.
This repo contains the code for paper "Dense reinforcement learning for safety validation of autonomous vehicles"
Deep Reinforcement Learning (PPO) in Autonomous Driving (Carla) [from scratch]
[CoRL 2021] Official implementation of paper "Safe Driving via Expert Guided Policy Optimization".
Creates an AWS DeepRacing training environment which can be deployed in the cloud, or locally on Ubuntu Linux, Windows or Mac.
A minimalist environment for decision-making in autonomous driving
[IEEE T-PAMI 2024] All you need for End-to-end Autonomous Driving
A unified, comprehensive and efficient recommendation library
推荐系统入门教程，在线阅读地址：https://datawhalechina.github.io/fun-rec/