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Adaptively Perturbed Mirror Descent for Learning in Games
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Adaptively Perturbed Mirror Descent for Learning in Games

International Conference on Machine Learning (ICML), 2023
Kenshi Abe
Kaito Ariu
Mitsuki Sakamoto
Atsushi Iwasaki
ArXiv (abs)PDFHTML

Papers citing "Adaptively Perturbed Mirror Descent for Learning in Games"

4 / 4 papers shown
Title
Multi-Objective Reinforcement Learning with Max-Min Criterion: A Game-Theoretic Approach
Multi-Objective Reinforcement Learning with Max-Min Criterion: A Game-Theoretic Approach
Woohyeon Byeon
Giseung Park
Jongseong Chae
Amir Leshem
Y. Sung
148
0
0
23 Oct 2025
Multi-Agent Q-Learning Dynamics in Random Networks: Convergence due to Exploration and Sparsity
A. Hussain
D. Leonte
Francesco Belardinelli
Raphael Huser
Dario Paccagnan
194
1
0
13 Mar 2025
COMAL: A Convergent Meta-Algorithm for Aligning LLMs with General Preferences
COMAL: A Convergent Meta-Algorithm for Aligning LLMs with General Preferences
Yongxu Liu
Argyris Oikonomou
Weiqiang Zheng
Yang Cai
Arman Cohan
291
3
0
30 Oct 2024
Last Iterate Convergence in Monotone Mean Field Games
Last Iterate Convergence in Monotone Mean Field Games
Noboru Isobe
Kenshi Abe
Kaito Ariu
487
0
0
07 Oct 2024