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Computation with Imprecise Probabilities

  • Lotfi A. Zadeh
Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Extended Abstract

An imprecise probability distribution is an instance of second-order uncertainty, that is, uncertainty about uncertainty, or uncertainty2 for short. Another instance is an imprecise possibility distribution . Computation with imprecise probabilities is not an academic exercise – it is a bridge to reality. In the real world, imprecise probabilities are the norm rather than exception. In large measure, real-world probabilities are perceptions of likelihood. Perceptions are intrinsically imprecise, reflecting the bounded ability of human sensory organs, and ultimately the brain, to resolve detail and store information.}

Keywords

Natural Language Generalize Constraint Possibility Distribution Extension Principle Precise Probability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. de Cooman G (2005) A behavioural model for vague probability assessments. Fuzzy Sets and Systems 154(3): 305–358CrossRefGoogle Scholar
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  3. Zadeh LA (1975) The Concept of a Linguistic Variable and its Applications to Approximate Reasoning—I. Information Sciences 8: 199–249CrossRefGoogle Scholar
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  6. Zadeh LA (2006) Generalized theory of uncertainty (GTU) —principal concepts and ideas. Computational Statistics & Data Analysis 51(1): 15–46CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Lotfi A. Zadeh
    • 1
  1. 1.Department of EECSUniversity of CaliforniaBerkeleyUSA

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