Abstract
Uncertainty plays an important role in decision making. People try to avoid risks introduced by uncertainty. Probability theory can model these risks, and information theory can measure these risks. Another type of uncertainty is ambiguity; where people are not aware of the probabilities. People also attempt to avoid ambiguity. Subjective logic can model ambiguity-based uncertainty using opinions. We look at extensions of information theory to measure the uncertainty of opinions.
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Muller, T., Wang, D., Jøsang, A. (2015). Information Theory for Subjective Logic. In: Torra, V., Narukawa, T. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2015. Lecture Notes in Computer Science(), vol 9321. Springer, Cham. https://doi.org/10.1007/978-3-319-23240-9_19
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DOI: https://doi.org/10.1007/978-3-319-23240-9_19
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