Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales

Terms and Conditions

Twitter GitHub LinkedIn Bluesky Youtube

© 2026 ResearchTrend.AI, All rights reserved.

Home
Papers
2303.03095
Cited By

Can We Find Nash Equilibria at a Linear Rate in Markov Games?

Can We Find Nash Equilibria at a Linear Rate in Markov Games?

International Conference on Learning Representations (ICLR), 2023

3 March 2023

ArXiv (abs)PDF HTML Github

Papers citing "Can We Find Nash Equilibria at a Linear Rate in Markov Games?"

4 / 4 papers shown

Multi-Objective Reinforcement Learning with Max-Min Criterion: A Game-Theoretic Approach

Multi-Objective Reinforcement Learning with Max-Min Criterion: A Game-Theoretic Approach

238

2

0

23 Oct 2025

Bilevel reinforcement learning via the development of hyper-gradient without lower-level convexity

Bilevel reinforcement learning via the development of hyper-gradient without lower-level convexity

500

10

0

30 May 2024

Last-Iterate Convergent Policy Gradient Primal-Dual Methods for
Constrained MDPs

Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPsNeural Information Processing Systems (NeurIPS), 2023

Alejandro Ribeiro

417

31

0

20 Jun 2023

Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games
with Bandit Feedback

Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit FeedbackNeural Information Processing Systems (NeurIPS), 2023

304

30

0

05 Mar 2023

Page 1 of 1