b'Tamer Basar'

research

∙ 09/09/2023

Global Convergence of Receding-Horizon Policy Search in Learning Estimator Designs

We introduce the receding-horizon policy gradient (RHPG) algorithm, the ...

0 Xiangyuan Zhang, et al. ∙

research

∙ 06/26/2023

Value of Information in Games with Multiple Strategic Information Providers

In the classical communication setting multiple senders having access to...

0 Raj Kiriti Velicheti, et al. ∙

research

∙ 03/16/2023

Large Population Games on Constrained Unreliable Networks

This paper studies an N–agent cost-coupled game where the agents are con...

0 Shubham Aggarwal, et al. ∙

research

∙ 02/25/2023

Revisiting LQR Control from the Perspective of Receding-Horizon Policy Gradient

We revisit in this paper the discrete-time linear quadratic regulator (L...

0 Xiangyuan Zhang, et al. ∙

research

∙ 01/30/2023

Learning the Kalman Filter with Fine-Grained Sample Complexity

We develop the first end-to-end sample complexity of model-free policy g...

0 Xiangyuan Zhang, et al. ∙

research

∙ 12/14/2022

Decentralized Nonconvex Optimization with Guaranteed Privacy and Accuracy

Privacy protection and nonconvexity are two challenging problems in dece...

0 Yongqiang Wang, et al. ∙

research

∙ 11/15/2022

An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods

In this paper, we revisit and improve the convergence of policy gradient...

0 Yanli Liu, et al. ∙

research

∙ 10/10/2022

Towards a Theoretical Foundation of Policy Optimization for Learning Control Policies

Gradient-based methods have been widely used for system design and optim...

0 Bin Hu, et al. ∙

research

∙ 09/26/2022

Weighted Age of Information based Scheduling for Large Population Games on Networks

In this paper, we consider a discrete-time multi-agent system involving ...

0 Shubham Aggarwal, et al. ∙

research

∙ 09/11/2022

Ensuring both Accurate Convergence and Differential Privacy in Nash Equilibrium Seeking on Directed Graphs

We study in this paper privacy protection in fully distributed Nash equi...

0 Yongqiang Wang, et al. ∙

research

∙ 08/24/2022

Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample Path

We consider online reinforcement learning in Mean-Field Games. In contra...

0 Muhammad Aneeq uz Zaman, et al. ∙

research

∙ 08/07/2022

Quantization enabled Privacy Protection in Decentralized Stochastic Optimization

By enabling multiple agents to cooperatively solve a global optimization...

4 Yongqiang Wang, et al. ∙

research

∙ 07/21/2022

Incentive Designs for Stackelberg Games with a Large Number of Followers and their Mean-Field Limits

We study incentive designs for a class of stochastic Stackelberg games w...

0 Sina Sanjari, et al. ∙

research

∙ 06/06/2022

Convergence and sample complexity of natural policy gradient primal-dual methods for constrained MDPs

We study sequential decision making problems aimed at maximizing the exp...

0 Dongsheng Ding, et al. ∙

research

∙ 06/05/2022

How does a Rational Agent Act in an Epidemic?

Evolution of disease in a large population is a function of the top-down...

0 S. Yagiz Olmez, et al. ∙

research

∙ 03/11/2022

Linear Quadratic Mean-Field Games with Communication Constraints

In this paper, we study a large population game with heterogeneous dynam...

0 Shubham Aggarwal, et al. ∙

research

∙ 01/20/2022

The Role of Gossiping for Information Dissemination over Networked Agents

We consider information dissemination over a network of gossiping agents...

0 Melih Bastopcu, et al. ∙

research

∙ 12/23/2021

Decentralized Multi-Task Stochastic Optimization With Compressed Communications

We consider a multi-agent network where each node has a stochastic (loca...

4 Navjot Singh, et al. ∙

research

∙ 12/15/2021

Finite-Sample Analysis of Decentralized Q-Learning for Stochastic Games

Learning in stochastic games is arguably the most standard and fundament...

0 Zuguang Gao, et al. ∙

research

∙ 11/19/2021

Modeling Presymptomatic Spread in Epidemics via Mean-Field Games

This paper is concerned with developing mean-field game models for the e...

0 S. Yagiz Olmez, et al. ∙

research

∙ 10/12/2021

On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning

Multi-agent reinforcement learning (MARL) algorithms often suffer from a...

0 Weichao Mao, et al. ∙

research

∙ 10/12/2021

Provably Efficient Reinforcement Learning in Decentralized General-Sum Markov Games

This paper addresses the problem of learning an equilibrium efficiently ...

0 Weichao Mao, et al. ∙

research

∙ 09/29/2021

Adversarial Linear-Quadratic Mean-Field Games over Multigraphs

In this paper, we propose a game between an exogenous adversary and a ne...

0 Muhammad Aneeq uz Zaman, et al. ∙

research

∙ 06/04/2021

Decentralized Q-Learning in Zero-sum Markov Games

We study multi-agent reinforcement learning (MARL) in infinite-horizon d...

0 Muhammed O. Sayin, et al. ∙

research

∙ 05/17/2021

The Confluence of Networks, Games and Learning

Recent years have witnessed significant advances in technologies and ser...

16 Tao Li, et al. ∙

research

∙ 03/30/2021

Reputation and Pricing Dynamics in Online Markets

We study the economic interactions among sellers and buyers in online ma...

0 Qian Ma, et al. ∙

research

∙ 01/04/2021

Derivative-Free Policy Optimization for Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity

Direct policy search serves as one of the workhorses in modern reinforce...

0 Kaiqing Zhang, et al. ∙

research

∙ 10/07/2020

Near-Optimal Regret Bounds for Model-Free RL in Non-Stationary Episodic MDPs

We consider model-free reinforcement learning (RL) in non-stationary Mar...

2 Weichao Mao, et al. ∙

research

∙ 09/09/2020

Reinforcement Learning in Non-Stationary Discrete-Time Linear-Quadratic Mean-Field Games

In this paper, we study large population multi-agent reinforcement learn...

0 Muhammad Aneeq uz Zaman, et al. ∙

research

∙ 07/15/2020

Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity

Model-based reinforcement learning (RL), which finds an optimal policy u...

27 Kaiqing Zhang, et al. ∙

research

∙ 06/08/2020

POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis

Monte-Carlo planning, as exemplified by Monte-Carlo Tree Search (MCTS), ...

0 Weichao Mao, et al. ∙

research

∙ 04/02/2020

Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning

Multi-agent reinforcement learning (MARL) under partial observability ha...

0 Weichao Mao, et al. ∙

research

∙ 03/30/2020

Approximate Equilibrium Computation for Discrete-Time Linear-Quadratic Mean-Field Games

While the topic of mean-field games (MFGs) has a relatively long history...

0 Muhammad Aneeq uz Zaman, et al. ∙

research

∙ 03/01/2020

Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks

This paper proposes a fully asynchronous scheme for policy evaluation of...

0 Xingyu Sha, et al. ∙

research

∙ 02/18/2020

Distributed Adaptive Newton Methods with Globally Superlinear Convergence

This paper considers the distributed optimization problem over a network...

0 Jiaqi Zhang, et al. ∙

research

∙ 12/09/2019

Decentralized Multi-Agent Reinforcement Learning with Networked Agents: Recent Advances

Multi-agent reinforcement learning (MARL) has long been a significant an...

0 Kaiqing Zhang, et al. ∙

research

∙ 11/24/2019

Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms

Recent years have witnessed significant advances in reinforcement learni...

0 Kaiqing Zhang, et al. ∙

research

∙ 11/03/2019

Non-Cooperative Inverse Reinforcement Learning

Making decisions in the presence of a strategic opponent requires one to...

0 Xiangyuan Zhang, et al. ∙

research

∙ 10/21/2019

Policy Optimization for H_2 Linear Control with H_∞ Robustness Guarantee: Implicit Regularization and Global Convergence

Policy optimization (PO) is a key ingredient for reinforcement learning ...

0 Kaiqing Zhang, et al. ∙

research

∙ 09/13/2019

Strategic Inference with a Single Private Sample

Motivated by applications in cyber security, we develop a simple game mo...

0 Erik Miehling, et al. ∙

research

∙ 08/06/2019

Online Planning for Decentralized Stochastic Control with Partial History Sharing

In decentralized stochastic control, standard approaches for sequential ...

0 Kaiqing Zhang, et al. ∙

research

∙ 07/22/2019

Optimal Hierarchical Signaling for Quadratic Cost Measures and General Distributions: A Copositive Program Characterization

In this paper, we address the problem of optimal hierarchical signaling ...

0 Muhammed O. Sayin, et al. ∙

research

∙ 07/06/2019

A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning

This paper considers a distributed reinforcement learning problem in whi...

0 Yixuan Lin, et al. ∙

research

∙ 06/19/2019

Global Convergence of Policy Gradient Methods to (Almost) Locally Optimal Policies

Policy gradient (PG) methods are a widely used reinforcement learning me...

0 Kaiqing Zhang, et al. ∙

research

∙ 05/31/2019

Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games

We study the global convergence of policy optimization for finding the N...

0 Kaiqing Zhang, et al. ∙

research

∙ 03/15/2019

A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning

This paper extends off-policy reinforcement learning to the multi-agent ...

0 Wesley Suttle, et al. ∙

research

∙ 02/09/2019

A Game of Drones: Cyber-Physical Security of Time-Critical UAV Applications with Cumulative Prospect Theory Perceptions and Valuations

The effective deployment of unmanned aerial vehicle (UAV) systems and se...

0 Anibal Sanjab, et al. ∙

research

∙ 02/04/2019

Deception-As-Defense Framework for Cyber-Physical Systems

We introduce deceptive signaling framework as a new defense measure agai...

0 Muhammed O. Sayin, et al. ∙

research

∙ 01/30/2019

A Game Theoretical Error-Correction Framework for Secure Traffic-Sign Classification

We introduce a game theoretical error-correction framework to design cla...

0 Muhammed O. Sayin, et al. ∙

research

∙ 01/30/2019

Robust Sensor Design Against Multiple Attackers with Misaligned Control Objectives

We introduce a robust sensor design framework to provide defense against...

0 Muhammed O. Sayin, et al. ∙

Tamer Basar

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