Last edited by Kazrazragore

Saturday, August 1, 2020 | History

5 edition of **Inductive logic programming** found in the catalog.

Inductive logic programming

ILP 2003 (2003 Szeged, Hungary)

- 114 Want to read
- 33 Currently reading

Published
**2003**
by Springer in Berlin, New York
.

Written in English

- Logic programming -- Congresses

**Edition Notes**

Includes bibliographical references and index.

Statement | Tamás Horváth, Akihiro Yamamoto (eds.). |

Genre | Congresses. |

Series | Lecture notes in computer science -- 2835. Lecture notes in artificial intelligence, Lecture notes in computer science -- 2835, Lecture notes in computer science |

Contributions | Horváth, Tamás, 1962-, Yamamoto, Akihiro, 1960- |

Classifications | |
---|---|

LC Classifications | QA76.63 .I52 2003 |

The Physical Object | |

Pagination | x, 400 p. : |

Number of Pages | 400 |

ID Numbers | |

Open Library | OL22572734M |

ISBN 10 | 3540201440 |

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Inductive Logic Programming. This book is an introduction to inductive logic programming (ILP), a research field at the intersection of machine learning and logic programming, which aims at a formal framework as well as practical algorithms for inductively learning relational descriptions in . Inductive Logic Programming and Embodied Agents: Possibilities and Limitations: /ch Open-ended learning is regarded as the ultimate milestone, especially in intelligent robotics. Preferably it should be unsupervised and it is by its natureCited by: 1.

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Inductive logic programming is a new research Inductive logic programming book 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.

May 20, · Interest in inductive logic programming has waxed and waned over the last decade, but never fallen to zero. This book is a summary of what was known in the field inand much has changed since then. It can however still serve as an introduction to the field of inductive logic programming, in spite of its publication date.4/5(1).

Jul 04, · Although Inductive Logic Programming (ILP) is generally thought of as a research area at the intersection of machine learning and computational logic, Bergadano and Gunetti propose that most of the research in ILP has in fact come from machine learning, particularly in the evolution of inductive reasoning from pattern recognition, through initial approaches to symbolic machine learning, to 5/5(2).

Inductive logic programming (ILP) is a subfield of symbolic artificial intelligence which uses logic programming as a uniform representation for examples, background knowledge and hypotheses. Given an encoding of the known background knowledge and a set of examples represented as a logical database of facts, an ILP system will derive a hypothesised logic program which entails all the positive.

Dec 26, · Read "Inductive Logic Programming 24th International Conference, ILPNancy, France, September, Revised Selected Papers" by available from Rakuten Kobo. This book constitutes the thoroughly refereed post-conference proceedings Brand: Springer International Publishing.

Probabilistic inductive logic programming aka. statistical relational learning addresses one of the central questions of artificial intelligence: the integration of probabilistic reasoning with machine learning and first order and relational logic.

Home Browse by Title Books Inductive Logic Programming: From Machine Learning to Software Engineering Inductive Logic Programming: From Machine Learning to Software Engineering November November This book constitutes the refereed conference proceedings of the 28th International Conference on Inductive Logic Programming, ILPheld in Ferrara, Italy, in September The 10 full papers presented were carefully reviewed and selected from numerous submissions.

Inductive Logic Programming (ILP) is a subfield of machine learning. Although Inductive Logic Programming (ILP) is generally thought of as a research area at the intersection of machine learning and computational logic, Bergadano and Gunetti propose that most of the research in ILP has in fact come from machine learning, particularly in the evolution of inductive reasoning from pattern recognition, through initial approaches to symbolic machine learning, to.

Whilst inheriting various positive characteristics of the parent subjects of logic programming and machine learning, it is hoped that inductive logic programming will overcome many of the limitations This book describes the theory, implementations and applications of this field.

Inductive programming (IP) is a special area of automatic programming, covering research from artificial intelligence and programming, which addresses learning of typically declarative (logic or functional) and often recursive programs from incomplete specifications, such as input/output examples or constraints.

Depending on the programming language used, there are several kinds of inductive. This book constitutes the thoroughly refereed post-conference proceedings of the 27th International Conference on Inductive Logic Programming, ILPheld in Orléans, France, in September The 12 full papers presented were carefully reviewed and selected from numerous submissions.

Inductive Logic Programming: Theory and Methods by Stephen Muggleton, Luc de Raedt. Publisher: ScienceDirect Number of pages: Description: Inductive Logic Programming is a new discipline which investigates the inductive construction of first-order clausal theories from examples and background knowledge.

An Introduction to Inductive Logic Programming. The material is suitable either as a reference book for researchers or as a textbook for a graduate course on the theoretical aspects of logic. Inductive Logic Programming given that logic programming had not yet come into existence. His major con- tributions were 1) the introduction of relative subsumption, a relationship of gen- erality between clauses and 2) the inductive mechanism of relative least general generalisation (RLGG).

Stephen Muggleton is the author of Inductive Logic Programming ( avg rating, 0 ratings, 0 reviews), Latest Advances in Inductive Logic Programming (0.

Dec 01, · This book represents a selection of papers presented at the Inductive Logic Programming (ILP) workshop held at Cumberland Lodge, Great Windsor Park. The collection marks two decades since the first ILP workshop in During this period the area. Aug 31, · Latest Advances In Inductive Logic Programming 1st Edition Read & Download - By Stephen Muggleton Latest Advances In Inductive Logic Programming This book represents a selection of papers presented at the Inductive Logic Programming (Ilp) wor - Read Online Books at justeetredehors.comhor: Stephen Muggleton.

This book constitutes the thoroughly refereed post-conference proceedings of the 25th International Conference on Inductive Logic Programming, ILPheld in Kyoto, Japan, in August The 14 revised papers presented were carefully reviewed and selected from 44 submissions.

The papers focus. Formally introduce Inductive Logic Programming (ILP) and its theoretical foundations Give an overall “feeling” of how it works Brieﬂy point out some alternative applications of ILP Manoel França (City University) Introduction to Inductive Logic Programming ML Group Meeting 9 /.

Inductive Logic Programming is a young and rapidly growing field combining machine learning and logic programming. This self-contained tutorial is the first theoretical introduction to ILP; it provides the reader with a rigorous and sufficiently broad basis for future research in the area/5(4).The inductive learning and logic programming sides of ILP (cont’) • Inductive logic programming extends the theory and practice of logic programming by investigating induction rather than deduction as the basic mode of inference – Logic programming theory describes deductive inference from.The Twelfth International Conference on Inductive Logic Programming was held in Sydney, Australia, July 9–11, The conference was colocated with two other events, the Nineteenth International Conference on Machine Learning (ICML) and the Fifteenth Annual Conference on Computational.