Data-driven control of COVID-19 in buildings: a reinforcement-learning approach

no code implementations • 27 Dec 2022 • Ashkan Haji Hosseinloo, Saleh Nabi, Anette Hosoi, Munther A. Dahleh

A general control framework is put forward for designing an optimal velocity field and proximal policy optimization, a reinforcement learning algorithm is employed to solve the control problem in a data-driven fashion.

reinforcement-learning Reinforcement Learning (RL)

Physics-Informed Koopman Network

no code implementations • 17 Nov 2022 • Yuying Liu, Aleksei Sholokhov, Hassan Mansour, Saleh Nabi

Koopman operator theory is receiving increased attention due to its promise to linearize nonlinear dynamics.

Reinforcement Learning State Estimation for High-Dimensional Nonlinear Systems

no code implementations • 29 Sep 2021 • Saviz Mowlavi, Mouhacine Benosman, Saleh Nabi

In high-dimensional nonlinear systems such as fluid flows, the design of state estimators such as Kalman filters relies on a reduced-order model (ROM) of the dynamics.

reinforcement-learning Reinforcement Learning (RL) +1

Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control

no code implementations • ICML 2018 • Yangchen Pan, Amir-Massoud Farahmand, Martha White, Saleh Nabi, Piyush Grover, Daniel Nikovski

Recent work has shown that reinforcement learning (RL) is a promising approach to control dynamical systems described by partial differential equations (PDE).

reinforcement-learning Reinforcement Learning (RL)