Machine Learning Guidance for Connection Tableaux

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F21%3A00350284" target="_blank" >RIV/68407700:21730/21:00350284 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/s10817-020-09576-7" target="_blank" >https://doi.org/10.1007/s10817-020-09576-7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10817-020-09576-7" target="_blank" >10.1007/s10817-020-09576-7</a>

Result language
angličtina
Original language name
Machine Learning Guidance for Connection Tableaux
Original language description
Connection calculi allow for very compact implementations of goal-directed proof search. We give an overview of our work related to connection tableaux calculi: first, we show optimised functional implementations of connection tableaux proof search, including a consistent Skolemisation procedure for machine learning. Then, we show two guidance methods based on machine learning, namely reordering of proof steps with Naive Bayesian probabilities, and expansion of a proof search tree with Monte Carlo Tree Search.
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
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/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)

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

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