Teaching Nash equilibrium with Python

The author describes an assignment in an undergraduate game theory course in which students work together in class to develop a computer algorithm to identify Nash equilibria. This assignment builds basic computer science skills while applying game theory knowledge to real-world situations. Students...

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Bibliographic Details
Published inThe Journal of economic education Vol. 54; no. 2; pp. 177 - 183
Main Author Luedtke, Allison Oldham
Format Journal Article
LanguageEnglish
Published Washington Routledge 03.04.2023
Taylor & Francis Inc
Subjects
Algorithms
Assignments
Computer Literacy
Computer Science
Cooperative Learning
Economics Education
Game Theory
games in the classroom
Nash equilibrium
Programming Languages
Undergraduate Students
Online AccessGet full text
ISSN0022-0485
2152-4068
DOI10.1080/00220485.2023.2168813

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Summary:The author describes an assignment in an undergraduate game theory course in which students work together in class to develop a computer algorithm to identify Nash equilibria. This assignment builds basic computer science skills while applying game theory knowledge to real-world situations. Students work as a team to delineate the steps and write a program to identify all of the pure-strategy Nash equilibria of the game. They then test this program by creating and solving their own game. This assignment represents an efficient way for undergraduate economics students to gain valuable computer science skills without assuming any pre-existing computer science knowledge, without having to take classes outside of the economics major, and without economics faculty having to restructure entire courses or curricula.
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ISSN:0022-0485
2152-4068
DOI:10.1080/00220485.2023.2168813