Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-45221-5_27 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
analogy,pattern recognition,theorem proving | Computer science,Automated theorem proving,Algorithm,Theoretical computer science,Mathematical proof,Analogy,ACL2,Lemma (mathematics) | Conference |
Citations | PageRank | References |
11 | 0.67 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| jose maria heras | 1 | 11 | 0.67 |
| Ekaterina Komendantskaya | 2 | 150 | 22.66 |
| Moa Johansson | 3 | 121 | 10.74 |
| Ewen Maclean | 4 | 38 | 4.77 |