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• W2146355964 abstract "Information is said to be bipolar when it has a positive and a negative part. The problem of representing and processing such bipolar information has recently received a lot of attention in uncertainty theories. In this paper, we are concerned with the representation of asymmetric bipolarity, i.e., with situations where positive and negative information are unrelated and processed in parallel. In this latter case, positive information consists of observations of experiment results, showing what values are possible, whereas negative information consists of constraints (e.g., provided by an expert), restricting the range of possible variable values. Up to now, there are no proposition as to how such bipolar information can be treated in the framework of imprecise probability theory, i.e., when information is represented by convex sets of probabilities. In this paper, we propose the basis of such a framework and provide some illustrative examples. © 2011 Wiley Periodicals, Inc." @default.
• W2146355964 created "2016-06-24" @default.
• W2146355964 creator A5070285963 @default.
• W2146355964 date "2011-03-17" @default.
• W2146355964 modified "2023-10-16" @default.
• W2146355964 title "Handling bipolar knowledge with imprecise probabilities" @default.
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• W2146355964 doi "https://doi.org/10.1002/int.20475" @default.
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