ResearchTrend.AI
Learning Nash Equilibria in Zero-Sum Stochastic Games via Entropy-Regularized Policy Approximation
v1v2 (latest)

Learning Nash Equilibria in Zero-Sum Stochastic Games via Entropy-Regularized Policy Approximation

Yue Guan
Qifan Zhang
Panagiotis Tsiotras
ArXiv (abs)PDFHTML

Papers citing "Learning Nash Equilibria in Zero-Sum Stochastic Games via Entropy-Regularized Policy Approximation"

3 / 3 papers shown
Title
Approximate Nash Equilibrium Learning for n-Player Markov Games in Dynamic Pricing
Approximate Nash Equilibrium Learning for n-Player Markov Games in Dynamic Pricing
Larkin Liu
90
1
0
13 Jul 2022
Survey of Recent Multi-Agent Reinforcement Learning Algorithms Utilizing Centralized Training
Survey of Recent Multi-Agent Reinforcement Learning Algorithms Utilizing Centralized Training
P. Sharma
Rolando Fernandez
Erin G. Zaroukian
M. Dorothy
Anjon Basak
Derrik E. Asher
72
42
0
29 Jul 2021
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators
Zaiwei Chen
S. T. Maguluri
Sanjay Shakkottai
Karthikeyan Shanmugam
OffRL
83
13
0
24 Jun 2021