## 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 102

O So far there has been no indication of how non - ground clauses enter the

addition to the restrictions we have placed on the class of clauses allowed in the

O So far there has been no indication of how non - ground clauses enter the

**theory**. We now proceed to introduce them . 3 . 3 Introducing predicates Inaddition to the restrictions we have placed on the class of clauses allowed in the

**theory**...Page 106

Proof of Proposition 9 . Our claim is that the algorithm produces a useful

for the model after it has seen the following facts : 1 . the representatives of all the

clauses in a learnable useful

...

Proof of Proposition 9 . Our claim is that the algorithm produces a useful

**theory**for the model after it has seen the following facts : 1 . the representatives of all the

clauses in a learnable useful

**theory**; 2 . subsets of all the clauses in 1 of size one...

Page 386

We ran 20 trials of FOCL with and without the domain

positive and 40 negative examples of illegal were randomly generated . Next , we

randomly introduced a number of errors into the domain

We ran 20 trials of FOCL with and without the domain

**theory**. On each trial , 40positive and 40 negative examples of illegal were randomly generated . Next , we

randomly introduced a number of errors into the domain

**theory**. Each operator ...### What people are saying - Write a review

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### Contents

Inductive Logic Programming | 4 |

A Framework for Inductive Logic Programming | 9 |

oor A | 22 |

Copyright | |

26 other sections not shown

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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