40 citations · 119 across the 19 of their papers we have counts for
5 papers · 1 filter
Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning
Yizhou Zhang, Guannan Qu, Pan Xu +3
We study a multi-agent reinforcement learning (MARL) problem where the agents interact over a given network. The goal of the agents is to cooperatively maximize the average of thei…
Bounded-Regret MPC via Perturbation Analysis: Prediction Error, Constraints, and Nonlinearity
Yiheng Lin, Yang Hu, Guannan Qu +2
We study Model Predictive Control (MPC) and propose a general analysis pipeline to bound its dynamic regret. The pipeline first requires deriving a perturbation bound for a finite-…
Online Adaptive Policy Selection in Time-Varying Systems: No-Regret via Contractive Perturbations
Yiheng Lin, James A. Preiss, Emile Anand +3
We study online adaptive policy selection in systems with time-varying costs and dynamics. We develop the Gradient-based Adaptive Policy Selection (GAPS) algorithm together with a…
Decentralized Online Convex Optimization in Networked Systems
Yiheng Lin, Judy Gan, Guannan Qu +2
We study the problem of networked online convex optimization, where each agent individually decides on an action at every time step and agents cooperatively seek to minimize the to…
Equipping Black-Box Policies with Model-Based Advice for Stable Nonlinear Control
Tongxin Li, Ruixiao Yang, Guannan Qu +3
Machine-learned black-box policies are ubiquitous for nonlinear control problems. Meanwhile, crude model information is often available for these problems from, e.g., linear approx…