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 198
Thus , induction of weak theories in a cumulative base logic is theoretically
always possible ; moreover , the Version Space can always be represented by its
boundaries ( there are no holes ) . On the other hand , we lose compositionality ...
Thus , induction of weak theories in a cumulative base logic is theoretically
always possible ; moreover , the Version Space can always be represented by its
boundaries ( there are no holes ) . On the other hand , we lose compositionality ...
Page 255
Experiments in non - monotonic first - order induction . In Proceedings of the First
International Workshop on Inductive Logic Programming ( pp . 195 - 206 ) .
Vienna de Castelo , Portugal : Unpublished , 1991 . [ 3 ] L . K . Branting .
Integrating ...
Experiments in non - monotonic first - order induction . In Proceedings of the First
International Workshop on Inductive Logic Programming ( pp . 195 - 206 ) .
Vienna de Castelo , Portugal : Unpublished , 1991 . [ 3 ] L . K . Branting .
Integrating ...
Page 424
1 Introduction Presented in this paper is a summary of the results of two
experiments in non - monotonic first - order induction . Common to both is the use
of a technique called Closed World Specialization ( CWS ) , described in Chapter
7 , this ...
1 Introduction Presented in this paper is a summary of the results of two
experiments in non - monotonic first - order induction . Common to both is the use
of a technique called Closed World Specialization ( CWS ) , described in Chapter
7 , this ...
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Contents
Inductive Logic Programming | 4 |
A Framework for Inductive Logic Programming | 9 |
oor A | 22 |
Copyright | |
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Common terms and phrases
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
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Bibliographic information
| Title | Inductive Logic Programming Issue 38 of A.P.I.C. studies in data processing, ISSN 0067-2483 Issue 38 of APIC Series, Automatic Programming Information Centre Brighton Volume 38 of Automatic Programming Information Centre Brighton: The APIC series |
| Editor | Stephen Muggleton |
| Edition | illustrated |
| Publisher | Academic Press, 1992 |
| Original from | the University of Michigan |
| Digitized | 16 Nov 2007 |
| ISBN | 0125097158, 9780125097154 |
| Length | 565 pages |
| Subjects | › › Computers / Intelligence (AI) & Semantics Computers / Programming / Object Oriented |
| Export Citation | BiBTeX EndNote RefMan |