A survey of world models for physical AI with uncertainty representation and control
A technical survey finds that reliable physical AI depends on co-designing learned world models, uncertainty representation, prediction horizons and closed-loop ...
A technical survey finds that reliable physical AI depends on co-designing learned world models, uncertainty representation, prediction horizons and closed-loop ...
A coupled material-flow model and local predictive controller reduced soybean cleaning loss, impurity and breakage in three field repetitions while ...
A simulation spanning 36 country, season and production-intensity scenarios found that jointly shifting lighting and climate control cut energy costs ...
A neural network predictive control framework that jointly optimizes thermal comfort, daylighting, energy use, and life-cycle cost cut a school ...
A new control framework for solar-integrated EV charging stations combines fuzzy logic, Kalman filtering, and predictive control to achieve high ...
A new MARL framework guided by MPC expert knowledge achieves coordinated frequency control across interconnected microgrids, with pass rates up ...
Control engineering rarely makes headlines, yet it is the invisible scaffolding holding up almost every technological promise of the modern ...
A new review shows how battery charge limits, motor capability, and tire grip must be coordinated to prevent dangerous torque ...
Researchers have developed an open-source, segment-by-segment heat exchanger model that matches industry-standard accuracy while running fast enough for real-time heat ...
The Rubik's Cube has long served as a demanding benchmark for autonomous systems precisely because it compresses so many difficulties ...
© 2025 Scienmag - Science Magazine
© 2025 Scienmag - Science Magazine