NDLI: Fuzzy ensembles for embedding adaptive behaviours in semi-autonomous avatars in 3D virtual worlds

Content Provider	IEEE Xplore Digital Library
Author	Wall, J. Izquierdo, E. Qianni Zhang
Copyright Year	2013
Description	Author affiliation: Multimedia & Vision Res. Group, Univ. of London, London, UK (Wall, J.; Izquierdo, E.; Qianni Zhang)
Abstract	Semi-autonomous avatars should be both realistic and believable. The goal is to learn from and reproduce the behaviours of the user-controlled input to enable semi-autonomous avatars to plausibly interact with their human-controlled counterparts. A powerful tool for embedding autonomous behaviour is learning by imitation. Hence, in this paper an ensemble of fuzzy inference systems cluster the user input data to identify natural groupings within the data to describe the users movement and actions in a more abstract way. Multiple clustering algorithms are investigated along with a neuro-fuzzy classifier; and an ensemble of fuzzy systems are evaluated.
Starting Page	1
Ending Page	6
File Size	3105394
Page Count	6
File Format	PDF
ISBN	9781467358071
ISSN	21653577
DOI	10.1109/ICDSP.2013.6622818
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-01
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Avatars Fuzzy logic Training Testing Three-dimensional displays Fuzzy systems Clustering algorithms virtual environments semi-autonomous avatar fuzzy inference system fuzzy ensembles
Content Type	Text
Resource Type	Article

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Fuzzy ensembles for embedding adaptive behaviours in semi-autonomous avatars in 3D virtual worlds