Abstract
This paper provides an introduction to the field of reasoning with uncertainty in Artificial Intelligence (AI), with an emphasis on reasoning with numeric uncertainty. The considered formalisms are Probability Theory and some of its generalizations, the Certainty Factor Model, Dempster-Shafer Theory, and Probabilistic Networks.
The investigations were carried out as part of the PIONIER-project Reasoning with Uncertainty, subsidized by the Netherlands Organization of Scientific Research (NWO), under grant pgs-22–262.
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© 1996 Springer-Verlag Berlin Heidelberg
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Voorbraak, F. (1996). Reasoning with uncertainty in AI. In: Dorst, L., van Lambalgen, M., Voorbraak, F. (eds) Reasoning with Uncertainty in Robotics. RUR 1995. Lecture Notes in Computer Science, vol 1093. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0013954
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DOI: https://doi.org/10.1007/BFb0013954
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