Abstract
Intelligent agents embedded in physical environments need the ability to connect, or anchor, the symbols used to perform abstract reasoning to the physical entities which these symbols refer to. Anchoring must rely on perceptual data which is inherently affected by uncertainty. We propose an anchoring technique based on the use of fuzzy sets to represent uncertainty, and of degree of subset-hood to compute the partial match between signatures of objects. We show examples where we use this technique to allow a deliberative system to reason about the objects (cars) observed by a vision system embarked in an unmanned helicopter, in the framework of the Witas project.
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References
H. Bandemer and W. Naether, editors. Fuzzy data analysis. Kluwer Academic, 1992.
I. Bloch. Information combination operators for data fusion: A comparative review with classification. IEEE Trans. on Systems, Man, and Cybernetics, A-26(1):52–67, 1996.
S. Coradeschi, L. Karlsson, and K. Nordberg. Integration of vision and decisionmaking in an autonomous airborne vehicle for traffic surveillance. In H. I. Christiansen, editor, Computer Vision Systems, volume 1542 of LNCS, pages 216–230, Berlin, Germany, 1999. Springer.
G. Klir and T. Folger. Fuzzy sets, uncertainty, and information. Prentice-Hall, 1988.
D. Kortenkamp, P. Bonasso, and R. Murphy, editors. Artificial Intelligence and Mobile Robots. MIT Press, Boston, MA, 1998.
E. H. Ruspini. On the semantics of fuzzy logic. Int. J. of Approximate Reasoning, 5:45–88, 1991.
A. Saffiotti. Pick-up what? In C. Bäckström and E. Sandewall, editors, Current Trends in AI Planning — Proc. of EWSP’ 93, pages 166–177. IOS Press, Amsterdam, NL, 1994.
S. Weber. A general concept of fuzzy connectives, negations and implications based on t-norms and t-conorms. Fuzzy sets and systems, 11:115–134, 1983.
WITAS web page: http://www.ida.liu.se/ext/witas/.
L. A. Zadeh. Fuzzy sets.Information and Control, 8:338–353, 1965.
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© 1999 Springer-Verlag Berlin Heidelberg
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Coradeschi, S., Saffiotti, A. (1999). Anchoring Symbols to Vision Data by Fuzzy Logic. In: Hunter, A., Parsons, S. (eds) Symbolic and Quantitative Approaches to Reasoning and Uncertainty. ECSQARU 1999. Lecture Notes in Computer Science(), vol 1638. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48747-6_10
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DOI: https://doi.org/10.1007/3-540-48747-6_10
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