A novel approach to studying strategic decisions with eye-tracking and machine learning
Michał Król , Magdalena Król
AbstractWe 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.
|Journal series||Judgment and Decision Making, ISSN 1930-2975, (A 35 pkt)|
|Publication size in sheets||0.65|
|Keywords in English||task recognition, eye-tracking, strategic games, machine learning|
|ASJC Classification||; ;|
|Publication indicators||: 2017 = 1.244; : 2017 = 2.525 (2) - 2017=2.868 (5)|
|Citation count*||42 (2020-11-28)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.