Proof-pattern recognition and lemma discovery in ACL2
Paper i proceeding, 2013

We present a novel technique for combining statistical machine learning for proof-pattern recognition with symbolic methods for lemma discovery. The resulting tool, ACL2(ml), gathers proof statistics and uses statistical pattern-recognition to pre-processes data from libraries, and then suggests auxiliary lemmas in new proofs by analogy with already seen examples. This paper presents the implementation of ACL2(ml) alongside theoretical descriptions of the proof-pattern recognition and lemma discovery methods involved in it.

Pattern recognition

Lemma discovery

Analogy

Theorem proving

Statistical machine-learning

Författare

J. Heras

University of Dundee

E. Komendantskaya

University of Dundee

Moa Johansson

Chalmers, Data- och informationsteknik, Programvaruteknik

E. Maclean

University of Edinburgh

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 8312 389-406

DOI

10.1007/978-3-642-45221-5_27

ISBN

978-3-642-45220-8

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2019-08-23