Search Results for author: Cezary Kaliszyk

Found 33 papers, 5 papers with code

The Isabelle ENIGMA

1 code implementation4 May 2022 Zarathustra A. Goertzel, Jan Jakubův, Cezary Kaliszyk, Miroslav Olšák, Jelle Piepenbrock, Josef Urban

We significantly improve the performance of the E automated theorem prover on the Isabelle Sledgehammer problems by combining learning and theorem proving in several ways.

Automated Theorem Proving

Learning Higher-Order Programs without Meta-Interpretive Learning

no code implementations29 Dec 2021 Stanisław J. Purgał, David M. Cerna, Cezary Kaliszyk

Learning complex programs through inductive logic programming (ILP) remains a formidable challenge.

Inductive logic programming

JEFL: Joint Embedding of Formal Proof Libraries

no code implementations21 Jul 2021 Qingxiang Wang, Cezary Kaliszyk

The heterogeneous nature of the logical foundations used in different interactive proof assistant libraries has rendered discovery of similar mathematical concepts among them difficult.

Online Machine Learning Techniques for Coq: A Comparison

no code implementations12 Apr 2021 Liao Zhang, Lasse Blaauwbroek, Bartosz Piotrowski, Prokop Černý, Cezary Kaliszyk, Josef Urban

Learning happens in an online manner, meaning that Tactician's machine learning model is updated immediately every time the user performs a step in an interactive proof.

Disambiguating Symbolic Expressions in Informal Documents

no code implementations ICLR 2021 Dennis Müller, Cezary Kaliszyk

We propose the task of disambiguating symbolic expressions in informal STEM documents in the form of LaTeX files - that is, determining their precise semantics and abstract syntax tree - as a neural machine translation task.

Language Modelling Machine Translation +1

A Study of Continuous Vector Representationsfor Theorem Proving

no code implementations22 Jan 2021 Stanisław Purgał, Julian Parsert, Cezary Kaliszyk

Applying machine learning to mathematical terms and formulas requires a suitable representation of formulas that is adequate for AI methods.

Automated Theorem Proving

Exploration of Neural Machine Translation in Autoformalization of Mathematics in Mizar

no code implementations5 Dec 2019 Qingxiang Wang, Chad Brown, Cezary Kaliszyk, Josef Urban

In our context informal mathematics refers to human-written mathematical sentences in the LaTeX format; and formal mathematics refers to statements in the Mizar language.

Machine Translation Translation

Property Invariant Embedding for Automated Reasoning

no code implementations27 Nov 2019 Miroslav Olšák, Cezary Kaliszyk, Josef Urban

This encoding represents symbols only by nodes in the graph, without giving the network any knowledge of the original labels.

Automated Theorem Proving

Can Neural Networks Learn Symbolic Rewriting?

no code implementations7 Nov 2019 Bartosz Piotrowski, Josef Urban, Chad E. Brown, Cezary Kaliszyk

This work investigates if the current neural architectures are adequate for learning symbolic rewriting.

Machine Translation Translation

Towards Finding Longer Proofs

1 code implementation30 May 2019 Zsolt Zombori, Adrián Csiszárik, Henryk Michalewski, Cezary Kaliszyk, Josef Urban

We present a reinforcement learning (RL) based guidance system for automated theorem proving geared towards Finding Longer Proofs (FLoP).

Automated Theorem Proving reinforcement-learning

GRUNGE: A Grand Unified ATP Challenge

1 code implementation6 Mar 2019 Chad E. Brown, Thibault Gauthier, Cezary Kaliszyk, Geoff Sutcliffe, Josef Urban

This paper describes a large set of related theorem proving problems obtained by translating theorems from the HOL4 standard library into multiple logical formalisms.

Logic in Computer Science

Reinforcement Learning of Theorem Proving

no code implementations NeurIPS 2018 Cezary Kaliszyk, Josef Urban, Henryk Michalewski, Mirek Olšák

The strongest version of the system is trained on a large corpus of mathematical problems and evaluated on previously unseen problems.

Automated Theorem Proving reinforcement-learning

First Experiments with Neural Translation of Informal to Formal Mathematics

no code implementations10 May 2018 Qingxiang Wang, Cezary Kaliszyk, Josef Urban

Our experiments show that our best performing model configurations are able to generate correct Mizar statements on 65. 73\% of the inference data, with the union of all models covering 79. 17\%.

Machine Translation Translation

Learning to Reason with HOL4 tactics

no code implementations2 Apr 2018 Thibault Gauthier, Cezary Kaliszyk, Josef Urban

Techniques combining machine learning with translation to automated reasoning have recently become an important component of formal proof assistants.


TacticToe: Learning to Prove with Tactics

no code implementations2 Apr 2018 Thibault Gauthier, Cezary Kaliszyk, Josef Urban, Ramana Kumar, Michael Norrish

We implement a automated tactical prover TacticToe on top of the HOL4 interactive theorem prover.

HolStep: A Machine Learning Dataset for Higher-order Logic Theorem Proving

1 code implementation1 Mar 2017 Cezary Kaliszyk, François Chollet, Christian Szegedy

We propose various machine learning tasks that can be performed on this dataset, and discuss their significance for theorem proving.

Automated Theorem Proving

Deep Network Guided Proof Search

no code implementations24 Jan 2017 Sarah Loos, Geoffrey Irving, Christian Szegedy, Cezary Kaliszyk

Here we suggest deep learning based guidance in the proof search of the theorem prover E. We train and compare several deep neural network models on the traces of existing ATP proofs of Mizar statements and use them to select processed clauses during proof search.

Game of Go Image Captioning +4

Semantic Parsing of Mathematics by Context-based Learning from Aligned Corpora and Theorem Proving

no code implementations29 Nov 2016 Cezary Kaliszyk, Josef Urban, Jiří Vyskočil

We study methods for automated parsing of informal mathematical expressions into formal ones, a main prerequisite for deep computer understanding of informal mathematical texts.

Automated Theorem Proving Semantic Parsing

Monte Carlo Tableau Proof Search

no code implementations18 Nov 2016 Michael Färber, Cezary Kaliszyk, Josef Urban

We study Monte Carlo Tree Search to guide proof search in tableau calculi.

Automated Theorem Proving

Proceedings First International Workshop on Hammers for Type Theories

no code implementations17 Jun 2016 Jasmin Christian Blanchette, Cezary Kaliszyk

This volume of EPTCS contains the proceedings of the First Workshop on Hammers for Type Theories (HaTT 2016), held on 1 July 2016 as part of the International Joint Conference on Automated Reasoning (IJCAR 2016) in Coimbra, Portugal.

Sharing HOL4 and HOL Light proof knowledge

no code implementations11 Sep 2015 Thibault Gauthier, Cezary Kaliszyk

When proving their properties, a human can often take inspiration from the existing formalized proofs available in other provers or libraries.

Premise Selection and External Provers for HOL4

no code implementations11 Sep 2015 Thibault Gauthier, Cezary Kaliszyk

Learning-assisted automated reasoning has recently gained popularity among the users of Isabelle/HOL, HOL Light, and Mizar.

Machine Learning of Coq Proof Guidance: First Experiments

no code implementations20 Oct 2014 Cezary Kaliszyk, Lionel Mamane, Josef Urban

We report the results of the first experiments with learning proof dependencies from the formalizations done with the Coq system.

Certified Connection Tableaux Proofs for HOL Light and TPTP

no code implementations20 Oct 2014 Cezary Kaliszyk, Josef Urban, Jiri Vyskocil

We discuss the differences between our direct implementation using an explicit Prolog stack, to the continuation passing implementation of MESON present in HOLLight and compare their performance on all core HOLLight goals.

Initial Experiments with TPTP-style Automated Theorem Provers on ACL2 Problems

no code implementations6 Jun 2014 Sebastiaan Joosten, Cezary Kaliszyk, Josef Urban

This paper reports our initial experiments with using external ATP on some corpora built with the ACL2 system.

Developing Corpus-based Translation Methods between Informal and Formal Mathematics: Project Description

no code implementations14 May 2014 Cezary Kaliszyk, Josef Urban, Jiri Vyskocil, Herman Geuvers

The goal of this project is to (i) accumulate annotated informal/formal mathematical corpora suitable for training semi-automated translation between informal and formal mathematics by statistical machine-translation methods, (ii) to develop such methods oriented at the formalization task, and in particular (iii) to combine such methods with learning-assisted automated reasoning that will serve as a strong semantic component.

Machine Translation Translation

Machine Learner for Automated Reasoning 0.4 and 0.5

no code implementations11 Feb 2014 Cezary Kaliszyk, Josef Urban, Jiří Vyskočil

Machine Learner for Automated Reasoning (MaLARea) is a learning and reasoning system for proving in large formal libraries where thousands of theorems are available when attacking a new conjecture, and a large number of related problems and proofs can be used to learn specific theorem-proving knowledge.

Automated Theorem Proving

Learning-assisted Theorem Proving with Millions of Lemmas

no code implementations11 Feb 2014 Cezary Kaliszyk, Josef Urban

We use these criteria to mine the large inference graph of the lemmas in the HOL Light and Flyspeck libraries, adding up to millions of the best lemmas to the pool of statements that can be re-used in later proofs.

Automated Theorem Proving

MizAR 40 for Mizar 40

no code implementations10 Oct 2013 Cezary Kaliszyk, Josef Urban

As a present to Mizar on its 40th anniversary, we develop an AI/ATP system that in 30 seconds of real time on a 14-CPU machine automatically proves 40% of the theorems in the latest official version of the Mizar Mathematical Library (MML).

Lemma Mining over HOL Light

no code implementations10 Oct 2013 Cezary Kaliszyk, Josef Urban

Analogously to the informal mathematical practice, only a tiny fraction of such statements is named and re-used in later proofs by formal mathematicians.

HOL(y)Hammer: Online ATP Service for HOL Light

1 code implementation19 Sep 2013 Cezary Kaliszyk, Josef Urban

HOL(y)Hammer is an online AI/ATP service for formal (computer-understandable) mathematics encoded in the HOL Light system.

Automated Theorem Proving

Learning-Assisted Automated Reasoning with Flyspeck

no code implementations29 Nov 2012 Cezary Kaliszyk, Josef Urban

The considerable mathematical knowledge encoded by the Flyspeck project is combined with external automated theorem provers (ATPs) and machine-learning premise selection methods trained on the proofs, producing an AI system capable of answering a wide range of mathematical queries automatically.

Cannot find the paper you are looking for? You can Submit a new open access paper.