The Emergence of Interactive Behaviour: A Model of Rational Menu Search

Xiuli Chen, Gilles Bailly, Duncan P. Brumby, Antti Oulasvirta, Andrew Howes

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

24 Citations (Scopus)

Abstract

One reason that human interaction with technology is difficult to understand is because the way in which people perform interactive tasks is highly adaptive. One such interactive task is menu search. In the current article we test the hypothesis that menu search is rationally adapted to (1) the ecological structure of interaction, (2) cognitive and perceptual limits, and (3) the goal to maximise the trade-off between speed and accuracy. Unlike in previous models, no assumptions are made about the strategies available to or adopted by users, rather the menu search problem is specified as a reinforcement learning problem and behaviour emerges by finding the optimal Markov Decision Process (MDP). The model is tested against existing empirical findings concerning the effect of menu organisation and menu length. The model predicts the effect of these variables on task completion time and eye movements. The discussion considers the pros and cons of the modelling approach relative to other well-known mod- elling approaches.
Original languageEnglish
Title of host publicationProceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15)
PublisherAssociation for Computing Machinery
Pages4217-4226
ISBN (Print)97814503-31456
DOIs
Publication statusPublished - 18 Apr 2015
Event33rd Annual ACM Conference on Human Factors in Computing Systems - Seaul, Korea, Korea, Democratic People's Republic of
Duration: 18 Apr 201523 Apr 2015

Conference

Conference33rd Annual ACM Conference on Human Factors in Computing Systems
Country/TerritoryKorea, Democratic People's Republic of
CitySeaul, Korea
Period18/04/1523/04/15

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