Learning Theorem Proving Components
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F21%3A00353686" target="_blank" >RIV/68407700:21730/21:00353686 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-030-86059-2_16" target="_blank" >https://doi.org/10.1007/978-3-030-86059-2_16</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-86059-2_16" target="_blank" >10.1007/978-3-030-86059-2_16</a>
Alternative languages
Result language
angličtina
Original language name
Learning Theorem Proving Components
Original language description
Saturation-style automated theorem provers (ATPs) based on the given clause procedure are today the strongest general reasoners for classical first-order logic. The clause selection heuristics in such systems are, however, often evaluating clauses in isolation, ignoring other clauses. This has changed recently by equipping the E/ENIGMA system with a graph neural network (GNN) that chooses the next given clause based on its evaluation in the context of previously selected clauses. In this work, we describe several algorithms and experiments with ENIGMA, advancing the idea of contextual evaluation based on learning important components of the graph of clauses.
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
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Automated Reasoning with Analytic Tableaux and Related Methods
ISBN
978-3-030-86058-5
ISSN
0302-9743
e-ISSN
0302-9743
Number of pages
13
Pages from-to
266-278
Publisher name
Springer
Place of publication
Cham
Event location
Birmingham
Event date
Sep 6, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000711656700016