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Title: Towards general models of player affect
Authors: Camilleri, Elizabeth
Yannakakis, Georgios N.
Liapis, Antonios
Keywords: Computer games -- Design
Level design (Computer science)
Active learning
Human-computer interaction
Artificial intelligence
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Camilleri, E., Yannakakis, G. N., & Liapis, A. (2017). Towards general models of player affect. Seventh International Conference on Affective Computing and Intelligent Interaction, San Antonio. 1-7.
Abstract: While the primary focus of affective computing has been on constructing efficient and reliable models of affect, the vast majority of such models are limited to a specific task and domain. This paper, instead, investigates how computational models of affect can be general across dissimilar tasks; in particular, in modeling the experience of playing very different video games. We use three dissimilar games whose players annotated their arousal levels on video recordings of their own playthroughs. We construct models mapping ranks of arousal to skin conductance and gameplay logs via preference learning and we use a form of cross-game validation to test the generality of the obtained models on unseen games. Our initial results comparing between absolute and relative measures of the arousal annotation values indicate that we can obtain more general models of player affect if we process the model output in an ordinal fashion.
Appears in Collections:Scholarly Works - InsDG

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