Cookies?
Library Header Image
LSE Research Online LSE Library Services

Automated equilibrium analysis of 2 × 2 × 2 games

Jahani, Sahar and von Stengel, Bernhard ORCID: 0000-0002-3488-8322 (2022) Automated equilibrium analysis of 2 × 2 × 2 games. In: Kanellopoulos, Panagiotis, Kyropoulou, Maria and Voudouris, Alexandros, (eds.) Algorithmic Game Theory - 15th International Symposium, SAGT 2022, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Science and Business Media Deutschland GmbH, pp. 223-237. ISBN 9783031157134

[img] Text (Automated Equilibrium Analysis of 2 × 2 × 2 Games) - Accepted Version
Download (759kB)

Identification Number: 10.1007/978-3-031-15714-1_13

Abstract

The set of all Nash equilibria of a non-cooperative game with more than two players is defined by equations and inequalities between nonlinear polynomials, which makes it challenging to compute. This paper presents an algorithm that computes this set for the simplest game with more than two players with arbitrary (possibly non-generic) payoffs, which has not been done before. We give new elegant formulas for completely mixed equilibria, and compute visual representations of the best-response correspondences and their intersections, which define the Nash equilibrium set. These have been implemented in Python and will be part of a public web-based software for automated equilibrium analysis. For small games, which are often studied in economic models, a complete Nash equilibrium analysis is desirable and should be feasible. This project demonstrates the difficulties of this task and offers pathways for extensions to larger games.

Item Type: Book Section
Additional Information: © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Divisions: Mathematics
Subjects: Q Science > QA Mathematics
Date Deposited: 13 Oct 2022 13:48
Last Modified: 31 May 2024 17:09
URI: http://eprints.lse.ac.uk/id/eprint/116978

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics