Probabilistic logic combines the capability of binary logic to express the structure of argument models with the capacity of probabilities to express degrees of truth of those arguments. The limitation of traditional probabilistic logic is that it is unable to express uncertainty about the probability values themselves. This paper provides a brief overview subjective logic which is a probabilistic logic that explicitly takes uncertainty about probability values into account. More specifically, we describe equivalent representations of uncertain probabilities, and their interpretations. Subjective logic is directly compatible with binary logic, probability calculus and classical probabilistic logic. The advantage of using subjective logic is that real world situations can be more realistically modelled, and that conclusions more correctly reflect the ignorance and uncertainties about the input arguments.
Cite as: Josang, A. (2007). Probabilistic Logic under Uncertainty. In Proc. Thirteenth Computing: The Australasian Theory Symposium (CATS2007), Ballarat, Australia. CRPIT, 65. Gudmundsson, J. and Jay, B., Eds. ACS. 101-110.
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