Actively Learning Reinforcement Learning: A Stochastic Optimal Control Approach

1 code implementation • 18 Sep 2023 • Mohammad S. Ramadan, Mahmoud A. Hayajnh, Michael T. Tolley, Kyriakos G. Vamvoudakis

In this paper we propose a framework towards achieving two intertwined objectives: (i) equipping reinforcement learning with active exploration and deliberate information gathering, such that it regulates state and parameter uncertainties resulting from modeling mismatches and noisy sensory; and (ii) overcoming the huge computational cost of stochastic optimal control.

Model Predictive Control reinforcement-learning