Suchergebnisse - Special Issue of the Inductive Logic Programming (ILP) 2019

Guest editors’ introduction: special issue on Inductive Logic Programming (ILP 2019) von Kazakov, Dimitar, Železný, Filip

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Inductive general game playing von Cropper, Andrew, Evans, Richard, Law, Mark

“… In the GGP competition, an agent is given the rules of a game (described as a logic program …”
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Learning higher-order logic programs von Cropper, Andrew, Morel, Rolf, Muggleton, Stephen

“… A key feature of inductive logic programming is its ability to learn first-order programs, which are intrinsically more expressive than propositional programs …”
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Logical reduction of metarules von Cropper, Andrew, Tourret, Sophie

“… Many forms of inductive logic programming (ILP) use metarules , second-order Horn clauses, to define the structure of learnable programs and thus the hypothesis space …”
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Propositionalization and embeddings: two sides of the same coin von Lavrač, Nada, Škrlj, Blaž, Robnik-Šikonja, Marko

“… Data preprocessing is an important component of machine learning pipelines, which requires ample time and resources. An integral part of preprocessing is data …”
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Transfer learning by mapping and revising boosted relational dependency networks von Azevedo Santos, Rodrigo, Paes, Aline, Zaverucha, Gerson

“… Statistical machine learning algorithms usually assume the availability of data of considerable size to train the models. However, they would fail in …”
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Constructing generative logical models for optimisation problems using domain knowledge von Srinivasan, Ashwin, Vig, Lovekesh, Shroff, Gautam

“… Here we investigate the use of Inductive Logic Programming (ILP) to construct models within a procedure that progressively …”
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Preface to special issue on Inductive Logic Programming, ILP 2017 and 2018 von Lachiche, Nicolas, Vrain, Christel, Riguzzi, Fabrizio, Bellodi, Elena, Zese, Riccardo

“… Inductive Logic Programming (ILP) is a field at the intersection of Machine Learning and Logic Programming, based on logic as a uniform representation language …”
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Learning efficient logic programs von Cropper, Andrew, Muggleton, Stephen H.

“… However, existing inductive logic programming (ILP) techniques cannot distinguish between the efficiencies of programs, such as permutation sort ( n !) and merge sort O ( n l o g n …”
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Lifted discriminative learning of probabilistic logic programs von Nguembang Fadja, Arnaud, Riguzzi, Fabrizio

“… Probabilistic logic programming (PLP) provides a powerful tool for reasoning with uncertain relational models …”
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Online probabilistic theory revision from examples with ProPPR von Guimarães, Victor, Paes, Aline, Zaverucha, Gerson

“… Handling relational data streams has become a crucial task, given the availability of pervasive sensors and Internet-produced content, such as social networks …”
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Semi-supervised online structure learning for composite event recognition von Michelioudakis, Evangelos, Artikis, Alexander, Paliouras, Georgios

“… In order to adapt graph-cut minimisation to first order logic, we employ a suitable structural distance for measuring the distance between sets of logical atoms …”
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Probabilistic and exact frequent subtree mining in graphs beyond forests von Welke, Pascal, Horváth, Tamás, Wrobel, Stefan

“… Motivated by the impressive predictive power of simple patterns, we consider the problem of mining frequent subtrees in arbitrary graphs. Although the …”
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Guest editors’ note

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