Abstract
Non-heuristic, numerical approaches to the formalization of uncertain knowledge are in general based on Probability Theory (Bayes or Upper/Lower), Fuzzy Set Theory or Dempster/Shafer Theory (according to Shafer or Smets). Assuming that each of these theories is an appropriate formalization of uncertain knowledge leads to the question: Which different aspects of uncertainty represent these theories ? Far answering this question a formalization of uncertain knowledge is necessary which allows the analysis of different uncertainty theories within one framework.
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Umkehrer, E., Schill, K. (1998). General Perspective on the Formalization of Uncertain Knowledge. In: Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach . International Series in Intelligent Technologies, vol 11. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5473-8_2
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DOI: https://doi.org/10.1007/978-1-4615-5473-8_2
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