Now showing items 1-2 of 2

    • Model-based Reinforcement Learning of Nonlinear Dynamical Systems 

      Farsi, Milad (University of Waterloo, 2022-01-25)
      Model-based Reinforcement Learning (MBRL) techniques accelerate the learning task by employing a transition model to make predictions. In this dissertation, we present novel techniques for online learning of unknown dynamics ...
    • Optimal Controller and Actuator Design for Nonlinear Parabolic Systems 

      Edalatzadeh, M. Sajjad; Morris, Kirsten (2019-10-08)
      Many physical systems are modeled by nonlinear parabolic differential equations, such as the Kuramoto-Sivashinsky (KS) equation. In this paper, the existence of a concurrent optimal controller and actuator design is ...

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