English

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

Computer Science and Game Theory 2023-12-19 v1 Artificial Intelligence Data Structures and Algorithms Machine Learning Theoretical Economics

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.

Keywords

Cite

@article{arxiv.2312.11063,
  title  = {A survey on algorithms for Nash equilibria in finite normal-form games},
  author = {Hanyu Li and Wenhan Huang and Zhijian Duan and David Henry Mguni and Kun Shao and Jun Wang and Xiaotie Deng},
  journal= {arXiv preprint arXiv:2312.11063},
  year   = {2023}
}

Comments

The published version is in Computer Science Review