AI Agent Training Framework
5.0k 2026-04-18
Gen-Verse/OpenClaw-RL
A fully asynchronous reinforcement learning framework to train personalized AI agents from natural conversation feedback and enable scalable real-world agentic RL.
Core Features
Train personalized AI agents through natural language conversations.
Fully asynchronous RL framework for efficient training.
Supports scalable agentic RL in terminal, GUI, SWE, and tool-call settings.
Zero API or GPU cost options, supporting local and cloud deployments.
Integrates various LLMs like Qwen3.5 and advanced RL methods.
Detailed Introduction
OpenClaw-RL revolutionizes AI agent training by offering a fully asynchronous reinforcement learning framework that transforms everyday conversations into powerful training signals. Unlike traditional batch-mode systems, it enables the creation of personalized agents through natural language feedback. Designed for real-world applications, it supports scalable agentic RL across diverse environments including terminal, GUI, software engineering, and tool-calling scenarios, with options for zero API/GPU costs and hybrid local/cloud deployment.