Concept learning is the induction of a de-scription from a set of examples. Inductive logic programming can be considered a spe-cial case of the general notion of concept learning specifically referring to the induction of first-order theories. Both concept learn-ing and inductive logic programming can be seen as a search over all possible sentences in some representation language for sentences that correctly explain the examples and also generalize to other sentences that are part of that concept. In this paper we explore in-ductive logic programming with equational logic as the representation language and ge-netic programming as the underlying search paradigm. Equational logic is the logic of substituting equals for equals with algebras a...
We extend the notion of anti-unification to cover equational theories and present a method based on ...
Equality plays an important role in our life, and we practise equational reasoning everyday. We can ...
We discuss the adoption of a three-valued setting for inductive concept learning. Distinguishing be...
Concept learning is the induction of a description from a set of examples. Inductive logic programmi...
Inductive machine learning suggests an alternative approach to the algebraic specification of softwa...
This paper presents an overview of recent systems for Inductive Logic Programming (ILP). After a sho...
technical reportThis thesis studies first-order unification in equational theories, called E-unifica...
Summary. This chapter provides a short overview of a GA-based system for in-ductive concept learning...
AbstractInductive Logic Programming (ILP) is the area of AI which deals with the induction of hypoth...
This paper presents a computational study of the change of the logic-based concepts to arithmeticbas...
Introducing equality into standard Horn clauses leads to a programming paradigm known as Equational ...
Three different formalizations of concept-learning in logic (as well as some variants) are analyzed ...
Inductive learning in First-Order Logic (FOL) is a hard task due to both the pro-hibitive size of th...
The representation language of Machine Learning has undergone a substantial evolution, starting fro...
An equational approach to the synthesis of functional and logic program is taken. Typically, the syn...
We extend the notion of anti-unification to cover equational theories and present a method based on ...
Equality plays an important role in our life, and we practise equational reasoning everyday. We can ...
We discuss the adoption of a three-valued setting for inductive concept learning. Distinguishing be...
Concept learning is the induction of a description from a set of examples. Inductive logic programmi...
Inductive machine learning suggests an alternative approach to the algebraic specification of softwa...
This paper presents an overview of recent systems for Inductive Logic Programming (ILP). After a sho...
technical reportThis thesis studies first-order unification in equational theories, called E-unifica...
Summary. This chapter provides a short overview of a GA-based system for in-ductive concept learning...
AbstractInductive Logic Programming (ILP) is the area of AI which deals with the induction of hypoth...
This paper presents a computational study of the change of the logic-based concepts to arithmeticbas...
Introducing equality into standard Horn clauses leads to a programming paradigm known as Equational ...
Three different formalizations of concept-learning in logic (as well as some variants) are analyzed ...
Inductive learning in First-Order Logic (FOL) is a hard task due to both the pro-hibitive size of th...
The representation language of Machine Learning has undergone a substantial evolution, starting fro...
An equational approach to the synthesis of functional and logic program is taken. Typically, the syn...
We extend the notion of anti-unification to cover equational theories and present a method based on ...
Equality plays an important role in our life, and we practise equational reasoning everyday. We can ...
We discuss the adoption of a three-valued setting for inductive concept learning. Distinguishing be...