Does Playing Against An Error Prone Opponent Influence Learning in Nim?

C. Nicholas McKinney and John van Huyck

Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), 2021, vol. 95, issue C

Abstract: When learning to play a game well, does it help to play against an opponent who makes the same sort of mistakes one tends to make or is it better to play against a procedurally rational algorithm, which never makes mistakes? This paper investigates subject performance in the game of Nim. We find evidence that subject performance improves more when playing against a human opponent than against a procedurally rational algorithm. We also find that subjects learn to recognize certain heuristics that improve their overall performance in more complex games.

Keywords: Bounded rationality; learning; heuristics; perfect information; Nim; human behavior; experiment (search for similar items in EconPapers)
JEL-codes: C72 C92 D83 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S2214804321001038
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:soceco:v:95:y:2021:i:c:s2214804321001038

DOI: 10.1016/j.socec.2021.101763

Access Statistics for this article

Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics) is currently edited by Pablo Brañas Garza

More articles in Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().