A novel approach to studying strategic decisions with eye-tracking and machine learning
Authors:
- Michał Król,
- Magdalena Król
Abstract
We propose a novel method of using eye-tracking to study strategic decisions. The conventional approach is to hypothesize what eye-patterns should be observed if a given model of decision-making was accurate, and then proceed to verify if this occurs. When such hypothesis specification is difficult a priori, we propose instead to expose subjects to a variant of the original strategic task that should induce processing it in a way consistent with the postulated model. It is then possible to use machine learning pattern recognition techniques to check if the associated eye-patterns are similar to those recorded during the original task. We illustrate the method using simple examples of 2x2 matching-pennies and coordination games with or without feedback about the counterparts’ past moves. We discuss the strengths and limitations of the method in this context.
- Record ID
- SWPSda654ce69f7e4e05be03cfaa482debed
- Author
- Journal series
- Judgment and Decision Making, ISSN 1930-2975
- Issue year
- 2017
- Vol
- 12
- No
- 6
- Pages
- 596-609
- Publication size in sheets
- 0.65
- Keywords in English
- task recognition, eye-tracking, strategic games, machine learning
- ASJC Classification
- ; ;
- URL
- http://journal.sjdm.org/17/17327/jdm17327.pdf opening in a new tab
- Language
- (en) English
- File
-
- File: 1
- 32. Król_JDM_2017.pdf
-
- Additional file
-
- File: 1
- 32a. oswiadczenie_jdm_2017_Król.pdf
-
- Score (nominal)
- 35
- Score source
- journalList
- Publication indicators
- : 2017 = 1.244; : 2017 = 2.525 (2) - 2017=2.868 (5); = 45
- Citation count
- 45
Share
- Uniform Resource Identifier
- http://192.168.13.97/info/article/SWPSda654ce69f7e4e05be03cfaa482debed/
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perishopening in a new tab system.