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Partial matching for analogy discovery in proofs and counter-examples

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Automated Deduction—CADE-14 (CADE 1997)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1249))

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Abstract

The problem of analogy in theorem proving has been studied for several years now (see [5, 10, 12] for example). Those works restrict the use of analogy to proofs, disregarding the possibilities of using analogy also for counter-examples construction. Moreover, they deal with the problem of proving a new theorem once an appropriate source theorem has been provided as a guideline. We overcome these drawbacks by using a method for model construction developed in our group and by generalizing proofs (or counter-examples constructions) before including them in the database of source examples. Analogy discovery relies on partial matching between a target statement, and a source (generalized) refutation or counter-example construction, thus allowing more targets to be regarded as “analogous” to a source. It increases the power of an analogy-based prover, by recognizing subgoals within a source refutation or model building. We use in this purpose notions of graph cut sets, and incremental update of statements.

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William McCune

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© 1997 Springer-Verlag Berlin Heidelberg

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Défourneaux, G., Peltier, N. (1997). Partial matching for analogy discovery in proofs and counter-examples. In: McCune, W. (eds) Automated Deduction—CADE-14. CADE 1997. Lecture Notes in Computer Science, vol 1249. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63104-6_43

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  • DOI: https://doi.org/10.1007/3-540-63104-6_43

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  • Print ISBN: 978-3-540-63104-0

  • Online ISBN: 978-3-540-69140-2

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