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On Tightness of Tsaknakis-Spirakis Descent Methods for Approximate Nash Equilibria

Authors :
Chen, Zhaohua
Deng, Xiaotie
Huang, Wenhan
Li, Hanyu
Li, Yuhao
Publication Year :
2021

Abstract

This article explores the minimum approximation ratio for Nash equilibrium in bi-matrix games, focusing on the Tsaknakis and Spirakis (TS) methods. The previous SOTA, TS algorithm, achieved an approximation ratio of 0.3393, but efforts to improve the analysis of the TS algorithm have been unsuccessful. This work demonstrates that the bound of 0.3393 is tight for the TS algorithm and presents a theoretical worst-case analysis. A condition for identifying tight instances is provided, along with a generator. While most generated instances are unstable, indicating potential improvements, stable instances exist where perturbations cannot enhance the 0.3393 bound. Other approximate algorithms, such as regret-matching and fictitious play, achieve better ratios on these instances. The generated instances can serve as benchmarks for approximate Nash equilibrium algorithms. The article also mentions progress in the TS algorithm, achieving an approximation ratio of 1/3, which can be further studied using the presented techniques.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2107.01471
Document Type :
Working Paper
Full Text :
https://doi.org/10.1016/j.ic.2023.105046