activity
20162020
most citedScalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward

23 citations · 27 across the 3 of their papers we have counts for

collaborators

9 papers

math.OC202023 cited

Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward

Guannan Qu, Yiheng Lin, Adam Wierman +1

It has long been recognized that multi-agent reinforcement learning (MARL) faces significant scalability issues due to the fact that the size of the state and action spaces are exp…

eess.SY2020

Online Residential Demand Response via Contextual Multi-Armed Bandits

Xin Chen, Yutong Nie, Na Li

Residential loads have great potential to enhance the efficiency and reliability of electricity systems via demand response (DR) programs. One major challenge in residential DR is…

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

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…