Gradient play in stochastic games: stationary points, convergence, and
sample complexity

Gradient play in stochastic games: stationary points, convergence, and sample complexity

1 June 2021

Na Li

Papers citing "Gradient play in stochastic games: stationary points, convergence, and sample complexity"

9 / 9 papers shown

Title
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions Chanwoo Park K. Zhang Asuman Ozdaglar 28 8 0 13 Jul 2023
Efficiently Computing Nash Equilibria in Adversarial Team Markov Games Fivos Kalogiannis Ioannis Anagnostides Ioannis Panageas Emmanouil-Vasileios Vlatakis-Gkaragkounis Vaggos Chatziafratis S. Stavroulakis 31 13 0 03 Aug 2022
Self-Play PSRO: Toward Optimal Populations in Two-Player Zero-Sum Games Stephen Marcus McAleer JB Lanier Kevin A. Wang Pierre Baldi Roy Fox T. Sandholm 27 18 0 13 Jul 2022
Convergence and Price of Anarchy Guarantees of the Softmax Policy Gradient in Markov Potential Games Dingyang Chen Qi Zhang Thinh T. Doan 15 12 0 15 Jun 2022
Learning in Congestion Games with Bandit Feedback Qiwen Cui Zhihan Xiong Maryam Fazel S. Du 24 12 0 04 Jun 2022
Independent Natural Policy Gradient Methods for Potential Games: Finite-time Global Convergence with Entropy Regularization Shicong Cen Fan Chen Yuejie Chi 27 15 0 12 Apr 2022
Convergence Rates of Two-Time-Scale Gradient Descent-Ascent Dynamics for Solving Nonconvex Min-Max Problems Thinh T. Doan 18 15 0 17 Dec 2021
Decentralized Cooperative Reinforcement Learning with Hierarchical Information Structure Hsu Kao Chen-Yu Wei V. Subramanian 13 12 0 01 Nov 2021
Independent Policy Gradient Methods for Competitive Reinforcement Learning C. Daskalakis Dylan J. Foster Noah Golowich 62 158 0 11 Jan 2021