Prolog Technology Reinforcement Learning Prover (System Description)
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F20%3A00346050" target="_blank" >RIV/68407700:21730/20:00346050 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-030-51054-1_33" target="_blank" >https://doi.org/10.1007/978-3-030-51054-1_33</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-51054-1_33" target="_blank" >10.1007/978-3-030-51054-1_33</a>
Alternative languages
Result language
angličtina
Original language name
Prolog Technology Reinforcement Learning Prover (System Description)
Original language description
We present a reinforcement learning toolkit for experiments with guiding automated theorem proving in the connection calculus. The core of the toolkit is a compact and easy to extend Prolog-based automated theorem prover called plCoP. plCoP builds on the leanCoP Prolog implementation and adds learning-guided Monte-Carlo Tree Search as done in the rlCoP system. Other components include a Python interface to plCoP and machine learners, and an external proof checker that verifies the validity of plCoP proofs. The toolkit is evaluated on two benchmarks and we demonstrate its extendability by two additions: (1) guidance is extended to reduction steps and (2) the standard leanCoP calculus is extended with rewrite steps and their learned guidance. We argue that the Prolog setting is suitable for combining statistical and symbolic learning methods. The complete toolkit is publicly released.
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
1611-3349
Number of pages
19
Pages from-to
489-507
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
000884319500033