  In this paper an output-feedback model-based reinforcement learning (MBRL)
method for a class of second-order nonlinear systems is developed. The control
technique uses exact model knowledge and integrates a dynamic state estimator
within the model-based reinforcement learning framework to achieve
output-feedback MBRL. Simulation results demonstrate the efficacy of the
developed method.
