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

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 variou...

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Vydáno v:Computer science review Ročník 51; s. 100613
Hlavní autoři: Li, Hanyu, Huang, Wenhan, Duan, Zhijian, Mguni, David Henry, Shao, Kun, Wang, Jun, Deng, Xiaotie
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Inc 01.02.2024
Témata:
Approximation algorithms
Game theory
Nash equilibrium
68Q25
68W40
91-08
Nash equilibrium
Approximation algorithms
68W25
Game theory
ISSN:1574-0137, 1876-7745
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Shrnutí: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. •A classification on Nash equilibrium algorithms in the literature with basic ideas on design and analysis presented.•A comprehensive comparison on Nash equilibrium algorithms in the literature over different kinds of games.•Practical suggestions on implementations and uses of Nash equilibrium algorithms.
ISSN:1574-0137
1876-7745
DOI:10.1016/j.cosrev.2023.100613