2026-07-23T05:28:39Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:18394 2024-03-06T11:01:47Z ddc:004 open_access

MizAR 60 for Mizar 50 Jakubův, Jan Chvalovský, Karel Goertzel, Zarathustra Kaliszyk, Cezary Olšák, Mirek Piotrowski, Bartosz Schulz, Stephan Suda, Martin Urban, Josef Mizar ENIGMA Automated Reasoning Machine Learning As a present to Mizar on its 50th anniversary, we develop an AI/TP system that automatically proves about 60% of the Mizar theorems in the hammer setting. We also automatically prove 75% of the Mizar theorems when the automated provers are helped by using only the premises used in the human-written Mizar proofs. We describe the methods and large-scale experiments leading to these results. This includes in particular the E and Vampire provers, their ENIGMA and Deepire learning modifications, a number of learning-based premise selection methods, and the incremental loop that interleaves growing a corpus of millions of ATP proofs with training increasingly strong AI/TP systems on them. We also present a selection of Mizar problems that were proved automatically. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Jan Jakubův and Karel Chvalovský and Zarathustra Goertzel and Cezary Kaliszyk and Mirek Olšák and Bartosz Piotrowski and Stephan Schulz and Martin Suda and Josef Urban 2023 Is Part Of LIPIcs, Volume 268, 14th International Conference on Interactive Theorem Proving (ITP 2023) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.ITP.2023.19 urn:nbn:de:0030-drops-183942 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITP.2023.19 eng https://creativecommons.org/licenses/by/4.0/legalcode