FEMaLeCoP: Fairly Efficient Machine Learning Connection Prover
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F15%3A00311239" target="_blank" >RIV/68407700:21730/15:00311239 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-662-48899-7_7" target="_blank" >http://dx.doi.org/10.1007/978-3-662-48899-7_7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-662-48899-7_7" target="_blank" >10.1007/978-3-662-48899-7_7</a>
Alternative languages
Result language
angličtina
Original language name
FEMaLeCoP: Fairly Efficient Machine Learning Connection Prover
Original language description
FEMaLeCoP is a connection tableau theorem prover based on leanCoP which uses efficient implementation of internal learning-based guidance for extension steps. Despite the fact that exhaustive use of such internal guidance can incur a significant slowdown of the raw inferencing process, FEMaLeCoP trained on related proofs can prove many problems that cannot be solved by leanCoP. In particular on the MPTP2078 benchmark, FEMaLeCoP adds 90 (15.7%) more problems to the 574 problems that are provable by leanCoP. FEMaLeCoP is thus the first AI/ATP system convincingly demonstrating that guiding the internal inference algorithms of theorem provers by knowledge learned from previous proofs can significantly improve the performance of the provers. This paper describes the system, discusses the technology developed, and evaluates the system.
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
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Logic for Programming, Artificial Intelligence, and Reasoning - 20th International Conference, LPAR-20 2015, Suva, Fiji, November 24-28, 2015, Proceedings
ISBN
978-3-662-48898-0
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
9
Pages from-to
88-96
Publisher name
Bertelsmann Springer CZ
Place of publication
Praha
Event location
Suva
Event date
Nov 24, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000375574900007