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Guiding an Instantiation Prover with Graph Neural Networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F23%3A00372206" target="_blank" >RIV/68407700:21730/23:00372206 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.29007/tp23" target="_blank" >https://doi.org/10.29007/tp23</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.29007/tp23" target="_blank" >10.29007/tp23</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Guiding an Instantiation Prover with Graph Neural Networks

  • Original language description

    In this work we extend an instantiation-based theorem prover iProver with machine learning (ML) guidance based on graph neural networks. For this we implement an interactive mode in iProver, which allows communication with an external agent via network sockets. The external (ML-based) agent guides the proof search by scoring generated clauses in the given clause loop. Our evaluation on a large set of Mizar problems shows that the ML guidance outperforms iProver’s standard human-programmed priority queues, solving more than twice as many problems in the same time. To our knowledge, this is the first time the performance of a state-of-the-art instantiation-based system is doubled by ML guidance.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of 24th International Conference on Logic for Programming, Artificial Intelligence and Reasoning (LPAR)

  • ISBN

  • ISSN

    2398-7340

  • e-ISSN

    2398-7340

  • Number of pages

    12

  • Pages from-to

    112-123

  • Publisher name

    EasyChair Publications

  • Place of publication

    Manchester

  • Event location

    Manizales

  • Event date

    Jun 4, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article