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

•This paper compares learning in the game of Nim when playing against error prone human opponents versus a procedurally rational computer algorithm.•We find evidence that subject performance improves more when playing against a human opponent than against a procedurally rational algorithm.•We find t...

Full description

Saved in:
Bibliographic Details
Published in:Journal of behavioral and experimental economics 2021-12, Vol.95, p.101763, Article 101763
Main Authors: McKinney, C. Nicholas, Van Huyck, John B.
Format: Article
Language:English
Subjects:
Algorithms
Bounded rationality
experiment
Game theory
Games
Heuristic
heuristics
human behavior
Learning
Nim
perfect information
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•This paper compares learning in the game of Nim when playing against error prone human opponents versus a procedurally rational computer algorithm.•We find evidence that subject performance improves more when playing against a human opponent than against a procedurally rational algorithm.•We find that subjects learn to recognize certain heuristics that improve their overall performance in more complex games. 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.
ISSN:2214-8043
2214-8051
DOI:10.1016/j.socec.2021.101763