Model-Based Control capability: online planning with offline learning

AI Impact Summary

This CAPABILITY introduces online planning driven by a model learned from offline data. It enables real-time decision-making while refining the underlying model with past experiences, improving sample efficiency and exploration safety. Suitable for robotics, autonomous systems, or any control-intensive application, the capability can shorten development cycles and improve performance under dynamic or uncertain conditions, assuming robust offline data pipelines and drift monitoring are in place.