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A survey on algorithms for Nash equilibria in finite normal-form games

  • Hanyu Li
  • , Wenhan Huang
  • , Zhijian Duan
  • , David Henry Mguni
  • , Kun Shao
  • , Jun Wang
  • , Xiaotie Deng*
  • *Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Abstract

Nash equilibrium is one of the most influential solution concepts in game theory. With the development of computer science and artificial intelligence, there is an increasing demand on Nash equilibrium computation, especially for Internet economics and multi-agent learning. This paper reviews various algorithms computing the Nash equilibrium and its approximation solutions in finite normal-form games from both theoretical and empirical perspectives. For the theoretical part, we classify algorithms in the literature and present basic ideas on algorithm design and analysis. For the empirical part, we present a comprehensive comparison on the algorithms in the literature over different kinds of games. Based on these results, we provide practical suggestions on implementations and uses of these algorithms. Finally, we present a series of open problems from both theoretical and practical considerations. © 2023 Elsevier Inc.
Original languageEnglish
Article number100613
Number of pages17
JournalComputer Science Review
Volume51
Online published28 Dec 2023
DOIs
Publication statusPublished - Feb 2024
Externally publishedYes

Funding

This work was supported by Science and Technology Innovation 2030 - “The New Generation of Artificial Intelligence” Major Project, China (No. 2022ZD0114904 ).

Research Keywords

  • Approximation algorithms
  • Game theory
  • Nash equilibrium

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