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Nonmonotomic Inductive Logic Programming
2001Nonmonotonic logic programming (NMLP) and inductive logic programming (ILP) are two important extensions of logic programming. The former aims at representing incomplete knowledge and reasoning with commonsense, while the latter targets the problem of inductive construction of a general theory from examples and background knowledge.
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Approaches to inductive logic programming
1992Inductive Logic Programming (ILP) is concerned with construction of logic programs from examples. It shares many concerns of Machine Learning (ML), but is committed to logic. As logic can help to provide a basis for elaborating such a methodology for learning, the area of ILP has attracted a wide attention of many researchers.
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Challenges for Inductive Logic Programming
1999Inductive logic programming (ILP) is a research area that has its roots in inductive machine learning and logic programming. Computational logic has significantly influenced machine learning through the field of inductive logic programming (ILP) which is concerned with the induction of logic programs from examples and background knowledge.
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Logic Programming and Co-inductive Definitions
2000This paper aims to define a complete semantics for a class of non-terminating logic programs. Standard approaches to deal with this problem consist in concentrating on programs where infinite derivations can be seen as computing, in the limit, some ”infinite object”. This is usually done by extending the domain of computation with infinite elements and
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A Review of Inductive Logic Programming Applications for Robotic Systems
Lecture Notes in Computer Science, 2023Martin E Müller
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An extended transformation approach to inductive logic programming
ACM Transactions on Computational Logic, 2001Nada Lavrač, Peter Flach
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Characterization of bio-chemical signals by inductive logic programming
Knowledge-Based Systems, 2002Andrei Doncescu +2 more
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Inductive logic programming and constraint logic programming (abstract)
1997openaire +1 more source
Inductive Logic Programming: Issues, results and the challenge of Learning Language in Logic
Artificial Intelligence, 1999Stephen Muggleton
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