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03/23/2023
Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems
The aim of this paper is to improve the understanding of the optimizatio...
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01/10/2023
Sequential Fair Resource Allocation under a Markov Decision Process Framework
We study the sequential decision-making problem of allocating a limited ...
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05/27/2022
Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games
We study the problem of finding the Nash equilibrium in a two-player zer...
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10/22/2021
A Reinforcement Learning Approach to Parameter Selection for Distributed Optimization in Power Systems
With the increasing penetration of distributed energy resources, distrib...
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10/21/2021
Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic Algorithm for Constrained Markov Decision Processes
We consider a discounted cost constrained Markov decision process (CMDP)...
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09/29/2021
A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning
We study a novel two-time-scale stochastic gradient method for solving o...
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10/28/2020
Finite-Time Analysis of Decentralized Stochastic Approximation with Applications in Multi-Agent and Multi-Task Learning
Stochastic approximation, a data-driven approach for finding the fixed p...
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06/08/2020
A Decentralized Policy Gradient Approach to Multi-task Reinforcement Learning
We develop a mathematical framework for solving multi-task reinforcement...
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02/19/2019