Towards Learning Infinite SMT Models (Work in Progress)
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F23%3A00380915" target="_blank" >RIV/68407700:21730/23:00380915 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/SYNASC61333.2023.00018" target="_blank" >https://doi.org/10.1109/SYNASC61333.2023.00018</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SYNASC61333.2023.00018" target="_blank" >10.1109/SYNASC61333.2023.00018</a>
Alternative languages
Result language
angličtina
Original language name
Towards Learning Infinite SMT Models (Work in Progress)
Original language description
This short paper proposes to learn models of satisfiability modulo theories (SMT) formulas during solving. Specifically, we focus on infinite models for problems in the logic of linear arithmetic with uninterpreted functions (UFLIA). The constructed models are piecewise linear. Such models are useful for satisfiable problems but also provide an alternative driver for model-based quantifier instantiation (MBQI).
Czech name
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Czech description
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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
<a href="/en/project/LL1902" target="_blank" >LL1902: Powering SMT Solvers by Machine Learning</a><br>
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
2023 25th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)
ISBN
979-8-3503-9413-9
ISSN
2470-8801
e-ISSN
2470-881X
Number of pages
4
Pages from-to
82-85
Publisher name
IEEE Industrial Electronic Society
Place of publication
Vienna
Event location
Nancy
Event date
Sep 11, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001223988300024