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European Workshop on Logics in Artificial Intelligence

JELIA 2004: Logics in Artificial Intelligence pp 526–538Cite as

Polynomial Approximations of Full Propositional Logic via Limited Bivalence

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3229))

Abstract

The aim of this paper is to study an anytime family of logics that approximates classical inference, in which every step in the approximation can be decided in polynomial time. For clausal logic, this task has been shown to be possible by Dalal [Dal96a,Dal96b]. However, Dalal’s approach cannot be applied to full classical logic.

In this paper we provide a family of logics, called Limited Bivalence Logics, that approximates full classical logic. Our approach contains two stages. In the first stage, a family of logics parameterised by a set of formulas Σ is presented. A lattice-based semantics is given and a sound and complete tableau-based proof-theory is developed. In the second stage, the first family is used to create another approximation family, in which every approximation step is shown to be polynomially decidable.

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Author information

Authors and Affiliations

  1. Computer Science Department, Institute of Mathematics and Statistics, University of São Paulo, Brazil

    Marcelo Finger

Authors
  1. Marcelo Finger
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Editor information

Editors and Affiliations

  1. CENTRIA, Universidade Nova de Lisboa, Portugal

    Jóse Júlio Alferes

  2. Departamento de Informática, Universidade Nova de Lisboa, 2829-516, Caparica, Portugal

    João Leite

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Finger, M. (2004). Polynomial Approximations of Full Propositional Logic via Limited Bivalence. In: Alferes, J.J., Leite, J. (eds) Logics in Artificial Intelligence. JELIA 2004. Lecture Notes in Computer Science(), vol 3229. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30227-8_44

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  • DOI: https://doi.org/10.1007/978-3-540-30227-8_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23242-1

  • Online ISBN: 978-3-540-30227-8

  • eBook Packages: Springer Book Archive

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