98 citations · 154 across the 15 of their papers we have counts for
6 papers · 1 filter
Inexact GMRES Policy Iteration for Large-Scale Markov Decision Processes
Matilde Gargiani, Dominic Liao-McPherson, Andrea Zanelli +1
Policy iteration enjoys a local quadratic rate of contraction, but its iterations are computationally expensive for Markov decision processes (MDPs) with a large number of states.…
Zero-Order Optimization for Gaussian Process-based Model Predictive Control
Amon Lahr, Andrea Zanelli, Andrea Carron +1
By enabling constraint-aware online model adaptation, model predictive control using Gaussian process (GP) regression has exhibited impressive performance in real-world application…
Asynchronous Computation of Tube-based Model Predictive Control
Jerome Sieber, Andrea Zanelli, Antoine P. Leeman +2
Tube-based model predictive control (MPC) methods bound deviations from a nominal trajectory due to uncertainties in order to ensure constraint satisfaction. While techniques that…
A Feasible Sequential Linear Programming Algorithm with Application to Time-Optimal Path Planning Problems
David Kiessling, Andrea Zanelli, Armin Nurkanović +5
In this paper, we propose a Feasible Sequential Linear Programming (FSLP) algorithm applied to time-optimal control problems (TOCP) obtained through direct multiple shooting discre…
Dynamic Programming Through the Lens of Semismooth Newton-Type Methods (Extended Version)
Matilde Gargiani, Andrea Zanelli, Dominic Liao-McPherson +2
Policy iteration and value iteration are at the core of many (approximate) dynamic programming methods. For Markov Decision Processes with finite state and action spaces, we show t…
PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation
Matilde Gargiani, Andrea Zanelli, Andrea Martinelli +2
Despite their success, policy gradient methods suffer from high variance of the gradient estimate, which can result in unsatisfactory sample complexity. Recently, numerous variance…