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20162021
most citedScalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward

23 citations · 36 across the 7 of their papers we have counts for

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Showing 2019Show all

7 papers · 1 filter

math.OC2019

Exploiting Fast Decaying and Locality in Multi-Agent MDP with Tree Dependence Structure

Guannan Qu, Na Li

This paper considers a multi-agent Markov Decision Process (MDP), where there are agents and each agent is associated with a state and action taking values from…

math.OC2019

Robust Hybrid Zero-Order Optimization Algorithms with Acceleration via Averaging in Time

Jorge I. Poveda, Na Li

We study novel robust zero-order algorithms with acceleration for the solution of real-time optimization problems. In particular, we propose a family of extremum seeking dynamics t…

math.OC2019

Distributed Zero-Order Algorithms for Nonconvex Multi-Agent Optimization

Yujie Tang, Junshan Zhang, Na Li

Distributed multi-agent optimization finds many applications in distributed learning, control, estimation, etc. Most existing algorithms assume knowledge of first-order information…

math.OC2019

On the Equivalence of Youla, System-level and Input-output Parameterizations

Yang Zheng, Luca Furieri, Antonis Papachristodoulou +2

A convex parameterization of internally stabilizing controllers is fundamental for many controller synthesis procedures. The celebrated Youla parameterization relies on a doubly-co…

math.OC2019

Online Optimal Control with Linear Dynamics and Predictions: Algorithms and Regret Analysis

Yingying Li, Xin Chen, Na Li

This paper studies the online optimal control problem with time-varying convex stage costs for a time-invariant linear dynamical system, where a finite lookahead window of accurate…

math.OC2019

Inducing Uniform Asymptotic Stability in Non-Autonomous Accelerated Optimization Dynamics via Hybrid Regularization

Jorge I. Poveda, Na Li

There have been many recent efforts to study accelerated optimization algorithms from the perspective of dynamical systems. In this paper, we focus on the robustness properties of…