Abstract
Evaluating the spatial behavior of players allows for comparing design intent with emergent behavior. However, spatial analytics for game development is still in its infancy and current analysis mostly relies on aggregate visualizations such as heatmaps. In this paper, we propose the use of advanced spatial clustering techniques to evaluate player behavior. In particular, we consider the use of DEDIC OM and DESICOM, two techniques that operate on asymmetric spatial similarity matrices and can simultaneously uncover preferred locations and likely transitions between them. Our results highlight the ability of asymmetric techniques to partition game maps into meaningful areas and to retain information about player movements between these areas.
Originalsprog | Engelsk |
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Titel | Proceedings of the 2014 IEEE Conference on Computational Intelligence in Games |
Antal sider | 8 |
Forlag | IEEE |
Publikationsdato | 2014 |
Sider | 44-52 |
ISBN (Trykt) | 978-1-4799-3546-8 |
DOI | |
Status | Udgivet - 2014 |
Begivenhed | IEEE Conference on Computational Intelligence and Games - Dortmund, Tyskland Varighed: 26 aug. 2014 → 29 aug. 2014 |
Konference
Konference | IEEE Conference on Computational Intelligence and Games |
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Land/Område | Tyskland |
By | Dortmund |
Periode | 26/08/2014 → 29/08/2014 |