Player behavioural modelling has grown from a means to improve the playing strength of computer programs that play classic games (e.g., chess), to a means for impacting the player experience and satisfaction in video games, as well as in cross-domain applications such as interactive storytelling. In this context, player behavioural modelling is concerned with two goals, namely (1) providing an interesting or effective game AI on the basis of player models and (2) creating a basis for game developers to personalise gameplay as a whole, and creating new user-driven game mechanics. In this article, we provide an overview of player behavioural modelling for video games by detailing four distinct approaches, namely (1) modelling player actions, (2) modelling player tactics, (3) modelling player strategies, and (4) player profiling. We conclude the article with an analysis on the applicability of the approaches for the domain of video games.
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With the increased adoption of real-time objective measurements of player experience, advances have been made in characterising the dynamically changing aspects of the player experience during gameplay itself. A direct coupling to player action, however, is not without challenges. Many physiological responses, for instance, have an inherent delay, and often take some time to return to a baseline, providing challenges of interpretation when analysing rapidly changing gameplay on a micro level of interaction. The development of event-related, or phasic, measurements directly coupled to player actions provides additional insights, for instance through player modelling, but also through the use of behavioural characteristics of the human computer interaction itself. In this study, we focused on the latter, and measured keyboard pressure in a number of different, fast-paced action games. In this particular case, we related specific functional game actions (keyboard presses) to experiential player behaviour. We found keyboard pressure to be higher for avoidance as compared to approach-oriented actions. Additionally, the difference between avoidance and approach keyboard pressure related to levels of arousal. The findings illustrate the application potential of qualifying players’ functional actions at play (navigating in a game) and interpret player experience related to these actions through players’ real world behavioural characteristics like interface pressure.
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Objectives Adherence to injury prevention programmes in football remains low, which is thought to drastically reduce the effects of injury prevention programmes. Reasons why (medical) staff and players implement injury prevention programmes, have been investigated, but player’s characteristics and perceptions about these programmes might influence their adherence. Therefore, this study investigated the relationships between player’s characteristics and adherence and between player’s perceptions and adherence following an implemented injury prevention programme. Methods Data from 98 of 221 football players from the intervention group of a cluster randomised controlled trial concerning hamstring injury prevention were analysed. Results Adherence was better among older and more experienced football players, and players considered the programme more useful, less intense, more functional and less time-consuming. Previous hamstring injuries, educational level, the programme’s difficulty and intention to continue the exercises were not significantly associated with adherence. Conclusion These player’s characteristics and perceptions should be considered when implementing injury prevention programmes.
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