Learned Provability Likelihood for Tactical Search

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F21%3A00353762" target="_blank" >RIV/68407700:21730/21:00353762 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.4204/EPTCS.342.7" target="_blank" >https://doi.org/10.4204/EPTCS.342.7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.4204/EPTCS.342.7" target="_blank" >10.4204/EPTCS.342.7</a>

Result language
angličtina
Original language name
Learned Provability Likelihood for Tactical Search
Original language description
We present a method to estimate the provability of a mathematical formula. We adapt the tactical theorem prover TacticToe to factor in these estimations. Experiments over the HOL4 library show an increase in the number of theorems re-proven by TacticToe thanks to this additional guidance. This amelioration in performance together with concurrent updates to the TacticToe framework lead to an improved user experience.
Czech name
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Czech description
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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)

Project
<a href="/en/project/GJ20-06390Y" target="_blank" >GJ20-06390Y: Powering Automatic Theorem Provers by Machine Learning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 9th International Symposium on Symbolic Computation in Software Science
ISBN
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ISSN
2075-2180
e-ISSN
2075-2180
Number of pages
8
Pages from-to
78-85
Publisher name
Electronic Proceedings in Theoretical Computer Science
Place of publication
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Event location
Linz
Event date
Sep 8, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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