
DerivativeFree Policy Optimization for RiskSensitive 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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NearOptimal Regret Bounds for ModelFree RL in NonStationary Episodic MDPs
We consider modelfree reinforcement learning (RL) in nonstationary Mar...
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Reinforcement Learning in NonStationary DiscreteTime LinearQuadratic MeanField Games
In this paper, we study large population multiagent reinforcement learn...
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ModelBased MultiAgent RL in ZeroSum Markov Games with NearOptimal Sample Complexity
Modelbased reinforcement learning (RL), which finds an optimal policy u...
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POLYHOOT: MonteCarlo Planning in Continuous Space MDPs with NonAsymptotic Analysis
MonteCarlo planning, as exemplified by MonteCarlo Tree Search (MCTS), ...
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Information State Embedding in Partially Observable Cooperative MultiAgent Reinforcement Learning
Multiagent reinforcement learning (MARL) under partial observability ha...
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Approximate Equilibrium Computation for DiscreteTime LinearQuadratic MeanField Games
While the topic of meanfield games (MFGs) has a relatively long history...
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Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks
This paper proposes a fully asynchronous scheme for policy evaluation of...
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Distributed Adaptive Newton Methods with Globally Superlinear Convergence
This paper considers the distributed optimization problem over a network...
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Decentralized MultiAgent Reinforcement Learning with Networked Agents: Recent Advances
Multiagent reinforcement learning (MARL) has long been a significant an...
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MultiAgent Reinforcement Learning: A Selective Overview of Theories and Algorithms
Recent years have witnessed significant advances in reinforcement learni...
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NonCooperative Inverse Reinforcement Learning
Making decisions in the presence of a strategic opponent requires one to...
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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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Strategic Inference with a Single Private Sample
Motivated by applications in cyber security, we develop a simple game mo...
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Online Planning for Decentralized Stochastic Control with Partial History Sharing
In decentralized stochastic control, standard approaches for sequential ...
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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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A CommunicationEfficient MultiAgent ActorCritic Algorithm for Distributed Reinforcement Learning
This paper considers a distributed reinforcement learning problem in whi...
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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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Policy Optimization Provably Converges to Nash Equilibria in ZeroSum Linear Quadratic Games
We study the global convergence of policy optimization for finding the N...
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A MultiAgent OffPolicy ActorCritic Algorithm for Distributed Reinforcement Learning
This paper extends offpolicy reinforcement learning to the multiagent ...
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A Game of Drones: CyberPhysical Security of TimeCritical UAV Applications with Cumulative Prospect Theory Perceptions and Valuations
The effective deployment of unmanned aerial vehicle (UAV) systems and se...
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DeceptionAsDefense Framework for CyberPhysical Systems
We introduce deceptive signaling framework as a new defense measure agai...
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A Game Theoretical ErrorCorrection Framework for Secure TrafficSign Classification
We introduce a game theoretical errorcorrection framework to design cla...
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Robust Sensor Design Against Multiple Attackers with Misaligned Control Objectives
We introduce a robust sensor design framework to provide defense against...
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CommunicationEfficient Distributed Reinforcement Learning
This paper studies the distributed reinforcement learning (DRL) problem ...
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FiniteSample Analyses for Fully Decentralized MultiAgent Reinforcement Learning
Despite the increasing interest in multiagent reinforcement learning (M...
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Distributed Learning of Average Belief Over Networks Using Sequential Observations
This paper addresses the problem of distributed learning of average beli...
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Revisiting Client Puzzles for State Exhaustion Attacks Resilience
In this paper, we address the challenges facing the adoption of client p...
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Resilient Output Synchronization of Heterogeneous Multiagent Systems under CyberPhysical Attacks
In this paper, we first describe, supported with analysis, the adverse e...
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On Remote Estimation with Multiple Communication Channels
This paper considers a sequential sensor scheduling and remote estimatio...
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Fully Decentralized MultiAgent Reinforcement Learning with Networked Agents
We consider the problem of fully decentralized multiagent reinforcement...
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Reliable Intersection Control in Noncooperative Environments
We propose a reliable intersection control mechanism for strategic auton...
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GraphTheoretic Framework for Unified Analysis of Observability and Data Injection Attacks in the Smart Grid
In this paper, a novel graphtheoretic framework is proposed to generali...
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Countries' Survival in Networked International Environments
This paper applies a recently developed power allocation game in Li and ...
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Generalized Colonel Blotto Game
Competitive resource allocation between adversarial decision makers aris...
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A GameTheoretic Method for MultiPeriod Demand Response: Revenue Maximization, Power Allocation, and Asymptotic Behavior
We study a multiperiod demand response management problem in the smart ...
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DiscreteTime Polar Opinion Dynamics with Susceptibility
This paper considers a discretetime opinion dynamics model in which eac...
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Strategic Communication Between Prospect Theoretic Agents over a Gaussian Test Channel
In this paper, we model a Stackelberg game in a simple Gaussian test cha...
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Evolution of Social Power in Social Networks with Dynamic Topology
The recently proposed DeGrootFriedkin model describes the dynamical evo...
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On the Analysis of the DeGrootFriedkin Model with Dynamic Relative Interaction Matrices
This paper analyses the DeGrootFriedkin model for evolution of the indi...
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AdaptiveRate Compressive Sensing Using Side Information
We provide two novel adaptiverate compressive sensing (CS) strategies f...
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Tamer Basar
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Professor, Director, Center for Advanced Study Interim Dean, College of Engineering at University of Illinois at UrbanaChampaign