Make E Smart Again (Short Paper)
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00346612" target="_blank" >RIV/68407700:21230/20:00346612 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/20:00346612
Result on the web
<a href="https://doi.org/10.1007/978-3-030-51054-1_26" target="_blank" >https://doi.org/10.1007/978-3-030-51054-1_26</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-51054-1_26" target="_blank" >10.1007/978-3-030-51054-1_26</a>
Alternative languages
Result language
angličtina
Original language name
Make E Smart Again (Short Paper)
Original language description
In this work in progress, we demonstrate a new use-case for the ENIGMA system. The ENIGMA system using the XGBoost implementation of gradient boosted decision trees has demonstrated high capability to learn to guide the E theorem prover’s inferences in real-time. Here, we strip E to the bare bones: we replace the KBO term ordering with an identity relation as the minimal possible ordering, disable literal selection, and replace evolved strategies with a simple combination of the clause weight and FIFO (first in first out) clause evaluation functions. We experimentally demonstrate that ENIGMA can learn to guide E as well as the smart, evolved strategies even without these standard automated theorem prover functionalities. To this end, we experiment with XGBoost’s meta-parameters over a dozen loops.
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/EF15_003%2F0000466" target="_blank" >EF15_003/0000466: Artificial Intelligence and Reasoning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science
ISBN
978-3-030-51053-4
ISSN
0302-9743
e-ISSN
0302-9743
Number of pages
8
Pages from-to
408-415
Publisher name
Springer
Place of publication
Cham
Event location
Paris
Event date
Jun 29, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000884319500026