Teaching Nash Equilibrium with Python

Autor/in	Luedtke, Allison Oldham
Titel	Teaching Nash Equilibrium with Python
Quelle	In: Journal of Economic Education, 54 (2023) 2, S.177-183 (7 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Luedtke, Allison Oldham)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0485
DOI	10.1080/00220485.2023.2168813
Schlagwörter	Undergraduate Students; Game Theory; Programming Languages; Assignments; Computer Literacy; Economics Education; Cooperative Learning + Suchen Sie Ihr Suchwort? Spieltheorie; Assignment; Auftrag; Zuweisung; Computerkenntnisse; Wirtschaftskunde; Kooperatives Lernen
Abstract	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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01