Correlated Boolean Operators for Uncertainty Logic
We present a correlated and gate which may be used to propagate uncertainty and dependence through Boolean functions, since any Boolean function may be expressed as a combination of and and not operations. We argue that the and gate is a bivariate copula family, which has the interpretation of const...
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Published in | Information Processing and Management of Uncertainty in Knowledge-Based Systems pp. 798 - 811 |
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Main Authors | , , , |
Format | Book Chapter |
Language | English |
Published |
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Springer International Publishing
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Series | Communications in Computer and Information Science |
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Abstract | We present a correlated and gate which may be used to propagate uncertainty and dependence through Boolean functions, since any Boolean function may be expressed as a combination of and and not operations. We argue that the and gate is a bivariate copula family, which has the interpretation of constructing bivariate Bernoulli random variables following a given Pearson correlation coefficient and marginal probabilities. We show how this copula family may be used to propagate uncertainty in the form of probabilities of events, probability intervals, and probability boxes, with only partial or no knowledge of the dependency between events, expressed as an interval for the correlation coefficient. These results generalise previous results by Fréchet on the conjunction of two events with unknown dependencies. We show an application propagating uncertainty through a fault tree for a pressure tank. This paper comes with an open-source Julia library for performing uncertainty logic. |
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AbstractList | We present a correlated and gate which may be used to propagate uncertainty and dependence through Boolean functions, since any Boolean function may be expressed as a combination of and and not operations. We argue that the and gate is a bivariate copula family, which has the interpretation of constructing bivariate Bernoulli random variables following a given Pearson correlation coefficient and marginal probabilities. We show how this copula family may be used to propagate uncertainty in the form of probabilities of events, probability intervals, and probability boxes, with only partial or no knowledge of the dependency between events, expressed as an interval for the correlation coefficient. These results generalise previous results by Fréchet on the conjunction of two events with unknown dependencies. We show an application propagating uncertainty through a fault tree for a pressure tank. This paper comes with an open-source Julia library for performing uncertainty logic. |
Author | Miralles-Dolz, Enrique Patelli, Edoardo Ferson, Scott Gray, Ander |
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ContentType | Book Chapter |
Copyright | Springer Nature Switzerland AG 2022 |
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DOI | 10.1007/978-3-031-08971-8_64 |
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PublicationTitle | Information Processing and Management of Uncertainty in Knowledge-Based Systems |
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Snippet | We present a correlated and gate which may be used to propagate uncertainty and dependence through Boolean functions, since any Boolean function may be... |
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StartPage | 798 |
SubjectTerms | Boolean functions Copula Imprecise probability Uncertainty logic Uncertainty propagation |
Title | Correlated Boolean Operators for Uncertainty Logic |
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