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Conflict-Driven Inductive Logic Programming [PDF]
Theory and Practice of Logic Programming, 2022 AbstractThe goal of inductive logic programming (ILP) is to learn a program that explains a set of examples. Until recently, most research on ILP targeted learning Prolog programs. The ILASP system instead learns answer set programs (ASP). Learning such expressive programs widens the applicability of ILP considerably; for example, enabling preference ...
Mark Law
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Inductive Logic Programming [PDF]
, 2011 This book constitutes the thoroughly refereed post-proceedings of the 20th International Conference on Inductive Logic Programming, ILP 2010, held in Florence, Italy in June 2010. The 11 revised full papers and 15 revised short papers presented together with abstracts of three invited talks were carefully reviewed and selected during two rounds of ...
FRASCONI, PAOLO, F. A. Lisi
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Knowledge discovery from structured mammography reports using inductive logic programming. [PDF]
AMIA Annu Symp Proc, 2005 Burnside ES +6 more
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Program Logics for Homogeneous Generative Run-Time Meta-Programming [PDF]
Logical Methods in Computer Science, 2015 This paper provides the first program logic for homogeneous generative run-time meta-programming---using a variant of MiniML by Davies and Pfenning as its underlying meta-programming language.
Martin Berger, Laurence Tratt
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Induction of Non-monotonic Logic Programs To Explain Statistical Learning Models [PDF]
Electronic Proceedings in Theoretical Computer Science, 2019 We present a fast and scalable algorithm to induce non-monotonic logic programs from statistical learning models. We reduce the problem of search for best clauses to instances of the High-Utility Itemset Mining (HUIM) problem.
Farhad Shakerin
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NUML International Journal of Engineering and Computing, 2023 Industries widely use three-phase inductive loads, such as induction motors, due to their cost-effectiveness, low maintenance, reliability, and durability.
Amir Hamza +4 more
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A History of Probabilistic Inductive Logic Programming
Frontiers in Robotics and AI, 2014 The field of Probabilistic Logic Programming (PLP) has seen significant advances in the last 20 years, with many proposals for languages that combine probability with logic programming.
Fabrizio eRiguzzi +2 more
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Symbolic AI for XAI: Evaluating LFIT Inductive Programming for Explaining Biases in Machine Learning
Computers, 2021 Machine learning methods are growing in relevance for biometrics and personal information processing in domains such as forensics, e-health, recruitment, and e-learning.
Alfonso Ortega +6 more
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Probabilistic Inductive Logic Programming [PDF]
, 2004 Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integration of probabilistic reasoning with first order logic representations and machine learning.
De Raedt, Luc, Kersting, Kristian
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