ROCK

ROCK is a scalable environment management framework designed specifically for agentic reinforcement learning applications. It utilizes a client-server architecture with robust isolation mechanisms to ensure stable and secure sandbox operations. The platform provides a unified SDK and is fully compatible with GEM protocols to standardize environment interactions.

ROCK (Reinforcement Open Construction Kit) is a distributed framework designed to manage scalable sandbox environments for agentic reinforcement learning. It addresses the complexity of environment lifecycle management by providing a client-server architecture that ensures stable, isolated execution through Docker-based containers. By implementing a layered service model—including Admin, Worker, and Rocklet components—the project enables researchers to standardize environment interactions while maintaining flexibility across different operating systems and deployment scenarios.