Probabilistic logic programming is a powerful technique to represent and reason with imprecise probabilistic knowledge. A probabilistic logic program (PLP) is a knowledge base whi...
Tabling is an implementation technique that improves the declarativeness and expressiveness of Prolog by reusing answers to subgoals. The declarative nature of tabled logic program...
Goals are used to define the behavior of (pro-active) agents. It is our view that the goals of an agent can be seen as a knowledge base of the situations that it wants to achieve. ...
The framework of multi-adjoint logic programming has shown to cover a number of approaches to reason under uncertainty, imprecise data or incomplete information. In previous works,...
Abstract. Inductive Logic Programming (ILP) has been applied to discover rules governing the three-dimensional topology of protein structure. The data-set unifies two sources of in...
Marcel Turcotte, Stephen Muggleton, Michael J. E. ...