Jan Jakubruv, Karel Chvalovsk'y, Z. Goertzel, C. Kaliszyk, Mirek Olvs'ak, Bartosz Piotrowski, S. Schulz, M. Suda, J. Urban
{"title":"开刀60到开刀50","authors":"Jan Jakubruv, Karel Chvalovsk'y, Z. Goertzel, C. Kaliszyk, Mirek Olvs'ak, Bartosz Piotrowski, S. Schulz, M. Suda, J. Urban","doi":"10.48550/arXiv.2303.06686","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":296683,"journal":{"name":"International Conference on Interactive Theorem Proving","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"MizAR 60 for Mizar 50\",\"authors\":\"Jan Jakubruv, Karel Chvalovsk'y, Z. Goertzel, C. Kaliszyk, Mirek Olvs'ak, Bartosz Piotrowski, S. Schulz, M. Suda, J. Urban\",\"doi\":\"10.48550/arXiv.2303.06686\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":296683,\"journal\":{\"name\":\"International Conference on Interactive Theorem Proving\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Interactive Theorem Proving\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.48550/arXiv.2303.06686\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Interactive Theorem Proving","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.48550/arXiv.2303.06686","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.