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@SafeRL-Lab

SAIL-Lab

Open Resource for Safe AI and Robot Learning Research.
README.md

Welcome to the Safe AI and Robot Learning (SAIL) Lab at UC Berkeley! 👋


 

What We Do

  • 🔭 We focus on the practice and theory of machine learning, with applications to foundation models and robotics. Our goal is to develop safe, reliable, and efficient systems that address pressing real-world challenges and drive impactful applications across diverse domains.

  • 🌱 We host workshops and seminars on agentic AI, safe AI, and robot learning. Researchers and students interested in safe AI and robot learning are welcome to join! Recordings are available on the AI Agent Research YouTube Channel. For more information, visit the Agentic AI Frontier Seminar, the Safe RL Seminar Homepage, and the Safe RL Workshop Homepage.

  • 📖 Our lab is guided by the principle of pursuing the essence of intelligence and bringing it into the real world.

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  1. Safe-MARL-in-Autonomous-Driving Safe-MARL-in-Autonomous-Driving Public

    [IEEE TAI] Safe Multi-Agent Reinforcement Learning to Make decisions in Autonomous Driving.

    Jupyter Notebook 105 12

  2. Robust-Gymnasium Robust-Gymnasium Public

    [ICLR 2025] Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning.

    Python 95 10

  3. agentic-web agentic-web Public

    Agentic Web: Weaving the Next Web with AI Agents.

    467 42

  4. cheetahclaws cheetahclaws Public

    CheetahClaws (Nano Claude Code): A Fast, Easy-to-Use, Production-Ready, Python-Native Personal AI Assistant for Any Model, Inspired by OpenClaw and Claude Code, Built to Work for You Autonomously 2…

    Python 645 245

  5. BenchNetRL BenchNetRL Public

    Benchmarking of Neural Network Architectures in Reinforcement Learning.

    Python 39 4

  6. AgenticPay AgenticPay Public

    AgenticPay: A Multi-Agent LLM Negotiation System for Buyer–Seller Transactions

    Python 25 9

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