Predicate logic as a modeling language: modeling and solving some machine learning and data mining problems withIDP3

DOI10.1017/S147106841400009XzbMath1379.68279arXiv1309.6883OpenAlexW2036981717MaRDI QIDQ4593015

Hendrik Blockeel, Stef de Pooter, Anthony Labarre, Broes de Cat, Marc Denecker, Maurice Bruynooghe, Bart Bogaerts, Sicco Verwer, Jan Ramon, Joachim Jansen

Publication date: 9 November 2017

Published in: Theory and Practice of Logic Programming (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1309.6883

zbMATH Keywords

stemmatologyknowledge representationlogic programmingphylogenetic treedeterministic finite-state automatondeclarative modelingknowledge-base systemsIDP system

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Logic in artificial intelligence (68T27) Knowledge representation (68T30) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20) Logic programming (68N17)

Related Items (10)

Shared aggregate sets in answer set programming ⋮ Stable-unstable semantics: Beyond NP with normal logic programs ⋮ The KB paradigm and its application to interactive configuration ⋮ Unnamed Item ⋮ Learning decision trees with flexible constraints and objectives using integer optimization ⋮ The Seventh Answer Set Programming Competition: Design and Results ⋮ Efficiently Coupling the I-DLV Grounder with ASP Solvers ⋮ IDP3 ⋮ Knowledge representation analysis of graph mining ⋮ Unsatisfiable Core Analysis and Aggregates for Optimum Stable Model Search

Uses Software

• MiniSat
• ML
• Smodels
• clasp
• Zinc
• Lua
• XSB
• IDP
• Essence

Cites Work

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