Inductive Logic Programming (ILP) is often situated as a research area emerging at the intersection of Machine Learning and Logic Programming (LP). This paper makes the link more clear between ILP and LP, in particular, between ILP and Abductive Logic Programming (ALP), i.e., LP extended with abductive reasoning. We formulate a generic framework for handling incomplete knowledge. This framework can be instantiated both to ALP and ILP approaches. By doing so more light is shed on the relationship between abduction and induction. As an example we consider the abductive procedure SLDNFA, and modify it into an inductive procedure which we call SLDNFAI. Keywords: Inductive Logic Programming, Abductive Logic Programming, Incomplete Knowledge, I...
We investigate how abduction and induction can be integrated into a common learning framework. In pa...
. This paper provides a brief introduction and overview of the emerging area of Inductive Constrain...
The representation language of Machine Learning has undergone a substantial evolution, starting fro...
We propose an approach for the integration of abduction and induction in Logic Programming. In parti...
We present the system LAP (Learning Abductive Programs) that is able to learn abductive logic progr...
We propose an approach for the integration of abduction and induction in Logic Programming. In parti...
The prospects of inductive logic programming (ILP) with respect to automatic programming (program sy...
We propose an approach for the integration of abduction and induction in Logic Programming. In parti...
We investigate how abduction and induction can be integrated into a common learning framework throug...
The prospects of inductive logic programming (ILP) with respect to automatic programming (program sy...
Inductive logic programming (ILP) is a form of machine learning. The goal of ILP is to induce a hypo...
Inductive logic programming (ILP) is a form of logic-based machine learning. The goal is to induce a...
AbstractInductive Logic Programming (ILP) is the area of AI which deals with the induction of hypoth...
Inductive Logic Programming (ILP) is a new discipline which investigates the inductive construction ...
We propose an approach for the integration of abduction and induction in Logic Programming. We defi...
We investigate how abduction and induction can be integrated into a common learning framework. In pa...
. This paper provides a brief introduction and overview of the emerging area of Inductive Constrain...
The representation language of Machine Learning has undergone a substantial evolution, starting fro...
We propose an approach for the integration of abduction and induction in Logic Programming. In parti...
We present the system LAP (Learning Abductive Programs) that is able to learn abductive logic progr...
We propose an approach for the integration of abduction and induction in Logic Programming. In parti...
The prospects of inductive logic programming (ILP) with respect to automatic programming (program sy...
We propose an approach for the integration of abduction and induction in Logic Programming. In parti...
We investigate how abduction and induction can be integrated into a common learning framework throug...
The prospects of inductive logic programming (ILP) with respect to automatic programming (program sy...
Inductive logic programming (ILP) is a form of machine learning. The goal of ILP is to induce a hypo...
Inductive logic programming (ILP) is a form of logic-based machine learning. The goal is to induce a...
AbstractInductive Logic Programming (ILP) is the area of AI which deals with the induction of hypoth...
Inductive Logic Programming (ILP) is a new discipline which investigates the inductive construction ...
We propose an approach for the integration of abduction and induction in Logic Programming. We defi...
We investigate how abduction and induction can be integrated into a common learning framework. In pa...
. This paper provides a brief introduction and overview of the emerging area of Inductive Constrain...
The representation language of Machine Learning has undergone a substantial evolution, starting fro...