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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Redesigning IT systems for specific user groups encompasses a lot of effort with respect to analysing and understanding user behaviour. The goal of this paper is to provide insights into patterns of behaviour of agricultural users, during the usage of a decision support system called OPTIRas (TM). This system aids agricultural users in their cultivar selection activities. We analyse logs resulting from OPTIRas (TM), and we get insights into user's navigational patterns. We claim that the results of our analysis can be used to support the redesign of decision support systems in order to address specific agricultural users' characteristics.
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(‘Co’-)Designing for healthy behaviour greatly benefits from integrating insights about individual behaviour and systemic influences. This study reports our experiences in using insights about individual and systemic determinants of behaviour to inform a large co-design project. To do so, we used two design tools that encourage focusing on individual determinants (Behavioural Lenses Approach) and social / systemic aspects of behaviour (Socionas). We performed a qualitative analysis to identify 1) when and how the team applied the design tools, and 2) how the tools supported or obstructed the design process. The results show that both tools had their distinctive uses during the process. Both tools improved the co-design process by deepening the conversations and underpinnings of the prototypes. Using the Behavioural Lenses under the guidance of a behavioural expert proved most beneficial. Furthermore, the Socionas showed the most potential when interacting with stakeholders, i.c. parents and PPTs.
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