ENIGMA: Efficient Learning-Based Inference Guiding Machine
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F17%3A00318950" target="_blank" >RIV/68407700:21730/17:00318950 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-319-62075-6_20" target="_blank" >https://doi.org/10.1007/978-3-319-62075-6_20</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-62075-6_20" target="_blank" >10.1007/978-3-319-62075-6_20</a>
Alternative languages
Result language
angličtina
Original language name
ENIGMA: Efficient Learning-Based Inference Guiding Machine
Original language description
ENIGMA is a learning-based method for guiding given clause selection in saturation-based theorem provers. Clauses from many previous proof searches are classified as positive and negative based on their participation in the proofs. An efficient classification model is trained on this data, classifying a clause as useful or un-useful for the proof search. This learned classification is used to guide next proof searches prioritizing useful clauses among other generated clauses. The approach is evaluated on the E prover and the CASC 2016 AIM benchmark, showing a large increase of E’s performance.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Intelligent Computer Mathematics
ISBN
978-3-319-62074-9
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
11
Pages from-to
292-302
Publisher name
Springer
Place of publication
Basel
Event location
Edinburgh
Event date
Jul 17, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000441207700020