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09/09/2023
Global Convergence of Receding-Horizon Policy Search in Learning Estimator Designs
We introduce the receding-horizon policy gradient (RHPG) algorithm, the ...
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06/26/2023
Value of Information in Games with Multiple Strategic Information Providers
In the classical communication setting multiple senders having access to...
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03/16/2023
Large Population Games on Constrained Unreliable Networks
This paper studies an N–agent cost-coupled game where the agents are con...
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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...
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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...
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12/14/2022
Decentralized Nonconvex Optimization with Guaranteed Privacy and Accuracy
Privacy protection and nonconvexity are two challenging problems in dece...
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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...
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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...
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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 ...
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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...
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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...
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08/07/2022
Quantization enabled Privacy Protection in Decentralized Stochastic Optimization
By enabling multiple agents to cooperatively solve a global optimization...
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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...
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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...
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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...
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03/11/2022
Linear Quadratic Mean-Field Games with Communication Constraints
In this paper, we study a large population game with heterogeneous dynam...
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01/20/2022
The Role of Gossiping for Information Dissemination over Networked Agents
We consider information dissemination over a network of gossiping agents...
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12/23/2021
Decentralized Multi-Task Stochastic Optimization With Compressed Communications
We consider a multi-agent network where each node has a stochastic (loca...
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12/15/2021
Finite-Sample Analysis of Decentralized Q-Learning for Stochastic Games
Learning in stochastic games is arguably the most standard and fundament...
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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...
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10/12/2021
On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning
Multi-agent reinforcement learning (MARL) algorithms often suffer from a...
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10/12/2021
Provably Efficient Reinforcement Learning in Decentralized General-Sum Markov Games
This paper addresses the problem of learning an equilibrium efficiently ...
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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...
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06/04/2021
Decentralized Q-Learning in Zero-sum Markov Games
We study multi-agent reinforcement learning (MARL) in infinite-horizon d...
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05/17/2021
The Confluence of Networks, Games and Learning
Recent years have witnessed significant advances in technologies and ser...
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03/30/2021
Reputation and Pricing Dynamics in Online Markets
We study the economic interactions among sellers and buyers in online ma...
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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...
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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...
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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...
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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...
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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), ...
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04/02/2020
Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning
Multi-agent reinforcement learning (MARL) under partial observability ha...
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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...
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03/01/2020
Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks
This paper proposes a fully asynchronous scheme for policy evaluation of...
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02/18/2020
Distributed Adaptive Newton Methods with Globally Superlinear Convergence
This paper considers the distributed optimization problem over a network...
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12/09/2019
Decentralized Multi-Agent Reinforcement Learning with Networked Agents: Recent Advances
Multi-agent reinforcement learning (MARL) has long been a significant an...
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11/24/2019
Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms
Recent years have witnessed significant advances in reinforcement learni...
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11/03/2019
Non-Cooperative Inverse Reinforcement Learning
Making decisions in the presence of a strategic opponent requires one to...
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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 ...
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09/13/2019
Strategic Inference with a Single Private Sample
Motivated by applications in cyber security, we develop a simple game mo...
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08/06/2019
Online Planning for Decentralized Stochastic Control with Partial History Sharing
In decentralized stochastic control, standard approaches for sequential ...
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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 ...
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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...
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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...
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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...
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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 ...
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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...
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02/04/2019
Deception-As-Defense Framework for Cyber-Physical Systems
We introduce deceptive signaling framework as a new defense measure agai...
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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...
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01/30/2019
