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11/16/2022
Asynchronous Gradient Play in Zero-Sum Multi-agent Games
Finding equilibria via gradient play in competitive multi-agent games ha...
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10/03/2022
Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games
Multi-Agent Reinforcement Learning (MARL) – where multiple agents learn ...
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04/12/2022
Independent Natural Policy Gradient Methods for Potential Games: Finite-time Global Convergence with Entropy Regularization
A major challenge in multi-agent systems is that the system complexity g...
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05/31/2021
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization
This paper investigates the problem of computing the equilibrium of comp...
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05/24/2021
Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence
Policy optimization, which learns the policy of interest by maximizing t...
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07/13/2020
Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization
Natural policy gradient (NPG) methods are among the most widely used pol...
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09/12/2019
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking
There is a growing interest in large-scale machine learning and optimiza...
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05/29/2019
Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data
Stochastic variance reduced methods have gained a lot of interest recent...
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03/09/2018