5 papers
Sample-Efficient Model-Free Policy Gradient Methods for Stochastic LQR via Robust Linear Regression
Bowen Song, Sebastien Gros, Andrea Iannelli
Policy gradient algorithms are widely used in reinforcement learning and belong to the class of approximate dynamic programming methods. This paper studies two key policy gradient…
Convergence Guarantees of Model-free Policy Gradient Methods for LQR with Stochastic Data
Bowen Song, Andrea Iannelli
Policy gradient (PG) methods are the backbone of many reinforcement learning algorithms due to their good performance in policy optimization problems. As a gradient-based approach,…
Hidden Convexity in Active Learning: A Convexified Online Input Design for ARX Systems
Nicolas Chatzikiriakos, Bowen Song, Philipp Rank +1
The goal of this work is to accelerate the identification of an unknown ARX system from trajectory data through online input design. Specifically, we present an active learning alg…
Robustness of Online Identification-based Policy Iteration to Noisy Data
Bowen Song, Andrea Iannelli
This article investigates the core mechanisms of indirect data-driven control for unknown systems, focusing on the application of policy iteration (PI) within the context of the li…
Convergence and Robustness of Value and Policy Iteration for the Linear Quadratic Regulator
Bowen Song, Chenxuan Wu, Andrea Iannelli
This paper revisits and extends the convergence and robustness properties of value and policy iteration algorithms for discrete-time linear quadratic regulator problems. In the mod…