Policy iteration using Q-functions: Linear dynamics with multiplicative noise¶
Authors: Peter Coppens, Panagiotis Patrinos
Published: 2022 ()
arXiv: 2212.01192
Summary¶
Abstract¶
This paper presents a novel model-free and fully data-driven policy iteration scheme for quadratic regulation of linear dynamics with state- and input-multiplicative noise. The implementation is similar to the least-squares temporal difference scheme for Markov decision processes, estimating Q-functions by solving a least-squares problem with instrumental variables. The scheme is compared with a model-based system identification scheme and natural policy gradient through numerical experiments.