A cognitive model of how people make decisions through interaction with visual displays

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper we report a cognitive model of how people make decisions through interaction. The model is based on the assumption that interaction for decision making is an example of a Partially Observable Markov Decision Process (POMDP) in which observations are made by limited perceptual systems that model human foveated vision and decisions are made by strategies that are adapted to the task. We illustrate the model by applying it to the task of determining whether to block a credit card given a number of variables including the location of a transaction, its amount, and the customer history. Each of these variables have a different validity and users may weight them accordingly. The model solves the POMDP by learning patterns of eye movements (strategies) adapted to different presentations of the data. We compare the model behavior to human performance on the credit card transaction task.

Bibliographic note

The paper presents an original, rigorous approach to modelling human decision making. The quality of the work was recognised by the SIGCHI 2017 conference, where this paper was awarded an Honorable Mention award, which means that it is ranked among the top 5% of the 2400 submissions. The work was conducted for a European Union project (SPEEDD) in which we worked with a company processing credit card data for international companies. In addition to helping the company refine their user interface designs and staff training, the research provides the basis for subsequent gaze-based analysis of user interfaces for decision support.


Original languageEnglish
Title of host publicationCHI '17
Subtitle of host publicationProceedings of the 2017 CHI Conference on Human Factors in Computing Systems
Publication statusPublished - 6 May 2017
EventACM CHI’17 Conference on Human Factors in Computing Systems - Denver, United States
Duration: 6 May 201711 May 2017


ConferenceACM CHI’17 Conference on Human Factors in Computing Systems
CountryUnited States