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Possibilistic logic as a logical framework for min-max discrete optimisation problems and prioritized constraints

  • Part II Selected Contributions
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Book cover Fundamentals of Artificial Intelligence Research (FAIR 1991)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 535))

Abstract

Possibilistic logic is basically a logic of uncertainty, but a significant fragment of it can also be seen as a logic for the representation of constraints with priorities. The gradation of inconsistency enables the definition of the "best" model(s) of a "partially inconsistent" set of possibilistic formulas. Many formal results have been proved for this fragment of possibilistic logic, including its axiomatisation. Besides, there are some well-adapted automated deduction procedures. Min-max discrete optimisation problems, and more generally problems with prioritized constraints, can be translated in this logical framework, and then solved by its automated deduction procedures.

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Authors and Affiliations

  1. Institut de Recherche en Informatique de Toulouse, Université Paul Sabatier, 31062, Toulouse Cedex, France

    Jérôome Lang

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  1. Jérôome Lang
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Philippe Jorrand Jozef Kelemen

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© 1991 Springer-Verlag Berlin Heidelberg

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Lang, J. (1991). Possibilistic logic as a logical framework for min-max discrete optimisation problems and prioritized constraints. In: Jorrand, P., Kelemen, J. (eds) Fundamentals of Artificial Intelligence Research. FAIR 1991. Lecture Notes in Computer Science, vol 535. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-54507-7_10

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  • DOI: https://doi.org/10.1007/3-540-54507-7_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54507-1

  • Online ISBN: 978-3-540-38420-5

  • eBook Packages: Springer Book Archive

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