Inductive Logic ProgrammingInductive logic programming is a new research area formed at the intersection of machine learning and logic programming. While the influence of logic programming has encouraged the development of strong theoretical foundations, this new area is inheriting its experimental orientation from machine learning. Inductive Logic Programming will be an invaluable text for all students of computer science, machine learning and logic programming at an advanced level. * * Examination of the background to current developments within the area * Identification of the various goals and aspirations for the increasing body of researchers in inductive logic programming * Coverage of induction of first order theories, the application of inductive logic programming and discussion of several logic learning programs * Discussion of the applications of inductive logic programming to qualitative modelling, planning and finite element mesh design |
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Page 256
Inducing temporal fault diagnostic rules from a qualitative model . In Proceedings
of the First International Workshop on Inductive Logic Programming ( pp . 243 -
258 ) . Vienna de Castelo , Portugal : Unpublished , 1991 . [ 17 ] N . S . Flann and
...
Inducing temporal fault diagnostic rules from a qualitative model . In Proceedings
of the First International Workshop on Inductive Logic Programming ( pp . 243 -
258 ) . Vienna de Castelo , Portugal : Unpublished , 1991 . [ 17 ] N . S . Flann and
...
Page 258
In Proceedings of the Fourth International Workshop on Machine Learning ( pp .
79 – 90 ) . Irvine , CA : Morgan Kaufmann , 1987 . [ 53 ] R . Seshu . Solving the
parity problem . In Proceedings of the Fourth European Working Session on ...
In Proceedings of the Fourth International Workshop on Machine Learning ( pp .
79 – 90 ) . Irvine , CA : Morgan Kaufmann , 1987 . [ 53 ] R . Seshu . Solving the
parity problem . In Proceedings of the Fourth European Working Session on ...
Page 393
In Proceedings of the Sixth Workshop on Machine Learning , pages 40 - 42 ,
Morgan Kaufmann , Ithaca , NY , 1989 . ... In Proceeding of the International
Machine Learning Workshop , pages 389 - 393 , Morgan - Kaufmann , Evanston ,
Il ...
In Proceedings of the Sixth Workshop on Machine Learning , pages 40 - 42 ,
Morgan Kaufmann , Ithaca , NY , 1989 . ... In Proceeding of the International
Machine Learning Workshop , pages 389 - 393 , Morgan - Kaufmann , Evanston ,
Il ...
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Contents
Inductive Logic Programming | 4 |
A Framework for Inductive Logic Programming | 9 |
oor A | 22 |
Copyright | |
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algorithm allows applied approach arguments assume background knowledge base body called CIGOL CLINT complete Computer concept consistent constrained atoms constraint constructed contains correct corresponding covers defined definition derivation described domain theory efficient equivalent examples exists explanation expression extend facts false Figure finite first-order formula function given GOLEM ground head Horn clauses hypothesis implied inductive inference input instances Intelligence introduced inverse knowledge knowledge base language least limit literals Logic Programming Machine Learning method Muggleton negative examples non-monotonic Note occur operator ordinary polynomial positive positive examples possible predicates present problem Proceedings proof properties prove queries reasoning relation replacing representation representative resolution respect restricted result rules saturation sentences similar sorted atoms space specialization specific step structure substitution symbol Theorem theory tree true values variables