We propose several algorithms for ecient Testing of logical Implication in the case of ground objects. Because the problem of Testing a set of propositional formulas for (un)satis ability is NP-complete there's strong evidence that there exist examples for which every algorithm which solves the problem of testing for (un)satis ability has a runtime that is exponential in the length of the input. So will have our algorithms. We will therefore point out classes of logic programs for which our algorithms have a lower runtime
We show that the satisfiability problem for the "symbolic heap" fragment of separation logic with ge...
The generic task of Inductive Logic Programming (ILP) is to search a predefined subspace of first-or...
The goal of inductive logic programming (ILP) is to search for a hypothesis that generalises trainin...
Abstract A new research area, Inductive Logic Programming, is presently emerging. While inheriting v...
It is widely accepted that many algorithms can be concisely and clearly expressed as logical inferen...
Inductive Logic Programming (ILP) is a subfield of Machine Learning with foundations in logic progra...
This thesis examines a novel induction-based frameworkfor logic programming. Limiting programs are l...
International audienceIn Inductive Logic Programming (ILP), algorithms that are purely of the bottom...
Inductive logic programming (ILP) is built on a foundation laid by research in machine learning and ...
Inductive Logic Programming (ILP) is a new discipline which investigates the inductive construction ...
AbstractCertain properties of logic programs are inexpressible in terms of their declarative semanti...
This paper describes applications of logic programming technology to the teaching of the inductive m...
We developed and implemented an inductive logic programming system and the first order classifier, c...
AbstractInductive Logic Programming (ILP) is the area of AI which deals with the induction of hypoth...
Abstract. We consider proof systems for effectively propositional logic. First, we show that proposi...
We show that the satisfiability problem for the "symbolic heap" fragment of separation logic with ge...
The generic task of Inductive Logic Programming (ILP) is to search a predefined subspace of first-or...
The goal of inductive logic programming (ILP) is to search for a hypothesis that generalises trainin...
Abstract A new research area, Inductive Logic Programming, is presently emerging. While inheriting v...
It is widely accepted that many algorithms can be concisely and clearly expressed as logical inferen...
Inductive Logic Programming (ILP) is a subfield of Machine Learning with foundations in logic progra...
This thesis examines a novel induction-based frameworkfor logic programming. Limiting programs are l...
International audienceIn Inductive Logic Programming (ILP), algorithms that are purely of the bottom...
Inductive logic programming (ILP) is built on a foundation laid by research in machine learning and ...
Inductive Logic Programming (ILP) is a new discipline which investigates the inductive construction ...
AbstractCertain properties of logic programs are inexpressible in terms of their declarative semanti...
This paper describes applications of logic programming technology to the teaching of the inductive m...
We developed and implemented an inductive logic programming system and the first order classifier, c...
AbstractInductive Logic Programming (ILP) is the area of AI which deals with the induction of hypoth...
Abstract. We consider proof systems for effectively propositional logic. First, we show that proposi...
We show that the satisfiability problem for the "symbolic heap" fragment of separation logic with ge...
The generic task of Inductive Logic Programming (ILP) is to search a predefined subspace of first-or...
The goal of inductive logic programming (ILP) is to search for a hypothesis that generalises trainin...