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CANOS: A Fast and Scalable Neural AC-OPF Solver Robust To N-1 Perturbations
Optimal Power Flow (OPF) refers to a wide range of related optimization problems with the goal of operating power systems efficiently and securely.
Controlling Commercial Cooling Systems Using Reinforcement Learning
This paper is a technical overview of DeepMind and Google's recent work on reinforcement learning for controlling commercial cooling systems.
Semi-analytical Industrial Cooling System Model for Reinforcement Learning
We present a hybrid industrial cooling system model that embeds analytical solutions within a multi-physics simulation.
On the role of planning in model-based deep reinforcement learning
These results indicate where and how to utilize planning in reinforcement learning settings, and highlight a number of open questions for future MBRL research.
Model-based Reinforcement Learning
reinforcement-learning
+1
