Adaptive user modelling in car racing games using behavioural and physiological data

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Title: Adaptive user modelling in car racing games using behavioural and physiological data
Authors: Georgiou, T
Demiris, Y
Item Type: Journal Article
Abstract: Personalised content adaptation has great potential to increase user engagement in video games. Procedural generation of user-tailored content increases the self-motivation of players as they immerse themselves in the virtual world. An adaptive user model is needed to capture the skills of the player and enable automatic game content altering algorithms to fit the individual user. We propose an adaptive user modelling approach using a combination of unobtrusive physiological data to identify strengths and weaknesses in user performance in car racing games. Our system creates user-tailored tracks to improve driving habits and user experience, and to keep engagement at high levels. The user modelling approach adopts concepts from the Trace Theory framework; it uses machine learning to extract features from the user’s physiological data and game-related actions, and cluster them into low level primitives. These primitives are transformed and evaluated into higher level abstractions such as experience, exploration and attention. These abstractions are subsequently used to provide track alteration decisions for the player. Collection of data and feedback from 52 users allowed us to associate key model variables and outcomes to user responses, and to verify that the model provides statistically significant decisions personalised to the individual player. Tailored game content variations between users in our experiments, as well as the correlations with user satisfaction demonstrate that our algorithm is able to automatically incorporate user feedback in subsequent procedural content generation.
Issue Date: 2-May-2017
Date of Acceptance: 12-Apr-2017
ISSN: 1573-1391
Publisher: Springer
Start Page: 267
End Page: 311
Journal / Book Title: User Modeling and User-Adapted Interaction
Volume: 27
Issue: 2
Copyright Statement: © The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Sponsor/Funder: Engineering & Physical Science Research Council (E
Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/P008461/1
Keywords: Science & Technology
Computer Science, Cybernetics
Computer Science
Personalised gaming
User modelling
Physiological models
Machine learning
User study
Theory of flow
Car racing game
Adaptive modelling
Information Systems
0801 Artificial Intelligence And Image Processing
0806 Information Systems
Publication Status: Published
Open Access location:
Appears in Collections:Electrical and Electronic Engineering

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