Abstract
A fuzzy colour model is defined to deal with human-machine communication situations where perceptual and conceptual deviations can appear. Logics have been defined to combine this model with the Probabilistic Reference And GRounding mechanism (PRAGR) (Mast and Wolter 2013) in order to obtain the most acceptable and appropriate colour descriptor depending on the situation. Two case studies are presented and promising results are obtained.
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Notes
- 1.
ISCC-NBS: http://tx4.us/nbs-iscc.htm (Accessed June 2017).
- 2.
Note that, given an open interval (analogously for another kind of interval) of finite dimension, there are two main ways to represent it: from the extreme points as (a, b) (classical notation) or as an open ball B\(_{r}\)(c) (Borelian notation) where \(c=(a+b)/2\) (centre) and \(r=(b-a)/2\) (radius).
- 3.
A Prolog program has been developed for connecting Fuzzy-QCD and PRAGR and it is available for download: https://sites.google.com/site/cogqda/publications.
- 4.
SWI-Prolog: http://www.swi-prolog.org/.
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Acknowledgements
This work was funded by the project Cognitive Qualitative Descriptions and Applications (CogQDA) at Universität Bremen. This research is partially supported by the projects of the Spanish Ministry of Economy and Competitiveness HERMES (TIN2013-46801-C4-1-R) and Simon (TIC-8052) of the Andalusian Regional Ministry of Economy, Innovation and Science. The authors also thank Vivien Mast for the use cases appearing in this paper.
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Falomir, Z., Gonzalez-Abril, L. (2017). A Fuzzy Colour Model Sensitive to the Context: Study Cases Using PRAGR and Logics. In: Torra, V., Narukawa, Y., Honda, A., Inoue, S. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2017. Lecture Notes in Computer Science(), vol 10571. Springer, Cham. https://doi.org/10.1007/978-3-319-67422-3_18
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