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Canonical Inference for Implicational Systems

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Automated Reasoning (IJCAR 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5195))

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Abstract

Completion is a general paradigm for applying inferences to generate a canonical presentation of a logical theory, or to semi-decide the validity of theorems, or to answer queries. We investigate what canonicity means for implicational systems that are axiomatizations of Moore families – or, equivalently, of propositional Horn theories. We build a correspondence between implicational systems and associative-commutative rewrite systems, give deduction mechanisms for both, and show how their respective inferences correspond. Thus, we exhibit completion procedures designed to generate canonical systems that are “optimal” for forward chaining, to compute minimal models, and to generate canonical systems that are rewrite-optimal. Rewrite-optimality is a new notion of “optimality” for implicational systems, one that takes contraction by simplification into account.

A longer version, “Canonical Ground Horn Theories”, is available as RR49/2007, DI, UniVR at http://profs.sci.univr.it/~bonacina/canonicity.html

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Alessandro Armando Peter Baumgartner Gilles Dowek

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Bonacina, M.P., Dershowitz, N. (2008). Canonical Inference for Implicational Systems. In: Armando, A., Baumgartner, P., Dowek, G. (eds) Automated Reasoning. IJCAR 2008. Lecture Notes in Computer Science(), vol 5195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71070-7_33

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  • DOI: https://doi.org/10.1007/978-3-540-71070-7_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71069-1

  • Online ISBN: 978-3-540-71070-7

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