The prospects of inductive logic programming (ILP) with respect to automatic programming (program synthesis) are discussed. We argue that logic program synthesis from incomplete information is but a niche of ILP, and study consequences of this statement. Then, three approaches are described: schema-driven synthesis of logic programs from incomplete specifications, the role of transformation techniques in ILP, and interactive assumption-based inductive learning
. This paper provides a brief introduction and overview of the emerging area of Inductive Constrain...
We develop a framework for stepwise synthesis of logic programs from incomplete specifications. Afte...
Inductive logic programming (ILP) is built on a foundation laid by research in machine learning and ...
The prospects of inductive logic programming (ILP) with respect to automatic programming (program sy...
AbstractThe inductive synthesis of recursive logic programs from incomplete information, such as inp...
The synthesis of recursive logic programs from incomplete information, such as input/output examples...
Inductive Logic Programming (ILP) is often situated as a research area emerging at the intersection ...
Inductive logic programming (ILP) is a form of logic-based machine learning. The goal is to induce a...
Inductive logic programming (ILP) is a form of machine learning. The goal of ILP is to induce a hypo...
AbstractInductive Logic Programming (ILP) is the area of AI which deals with the induction of hypoth...
We propose an approach for the integration of abduction and induction in Logic Programming. In parti...
Inductive Logic Programming (ILP) is a new discipline which investigates the inductive construction ...
. In this paper we suggest a mechanism that improves significantly the performance of a top-down in...
The current paper presents a brief overview of Inductive logic programming (ILP) systems. ILP algori...
Inductive Logic Programming (ILP) is a subfield of Machine Learning with foundations in logic progra...
. This paper provides a brief introduction and overview of the emerging area of Inductive Constrain...
We develop a framework for stepwise synthesis of logic programs from incomplete specifications. Afte...
Inductive logic programming (ILP) is built on a foundation laid by research in machine learning and ...
The prospects of inductive logic programming (ILP) with respect to automatic programming (program sy...
AbstractThe inductive synthesis of recursive logic programs from incomplete information, such as inp...
The synthesis of recursive logic programs from incomplete information, such as input/output examples...
Inductive Logic Programming (ILP) is often situated as a research area emerging at the intersection ...
Inductive logic programming (ILP) is a form of logic-based machine learning. The goal is to induce a...
Inductive logic programming (ILP) is a form of machine learning. The goal of ILP is to induce a hypo...
AbstractInductive Logic Programming (ILP) is the area of AI which deals with the induction of hypoth...
We propose an approach for the integration of abduction and induction in Logic Programming. In parti...
Inductive Logic Programming (ILP) is a new discipline which investigates the inductive construction ...
. In this paper we suggest a mechanism that improves significantly the performance of a top-down in...
The current paper presents a brief overview of Inductive logic programming (ILP) systems. ILP algori...
Inductive Logic Programming (ILP) is a subfield of Machine Learning with foundations in logic progra...
. This paper provides a brief introduction and overview of the emerging area of Inductive Constrain...
We develop a framework for stepwise synthesis of logic programs from incomplete specifications. Afte...
Inductive logic programming (ILP) is built on a foundation laid by research in machine learning and ...