Bandit-based Monte-Carlo structure learning of probabilistic logic programs

DOI10.1007/s10994-015-5510-3zbMath1346.68051OpenAlexW1200217156WikidataQ58063645 ScholiaQ58063645MaRDI QIDQ894703

Elena Bellodi, Fabrizio Riguzzi, Nicola Di Mauro

Publication date: 2 December 2015

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-015-5510-3

zbMATH Keywords

structure learningstatistical relational learningMonte Carlo tree searchmulti-armed bandit problemdistribution semanticslogic programs with annotated disjunctions

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Markov and semi-Markov decision processes (90C40) Logic programming (68N17)

Related Items (3)

Lifted discriminative learning of probabilistic logic programs ⋮ Using SWISH to Realize Interactive Web-based Tutorials for Logic-based Languages ⋮ Probabilistic inductive constraint logic

Uses Software

• MapReduce
• ProbLog
• YAP-Prolog
• PITA
• FactorBase

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