Inductive Logic Programming (ILP) is a combination of inductive learning and first-order logic aiming to learn first-order hypotheses from training examples. ILP has a serious b...
We investigate the discrete (finite) case of the Popper-Renyi theory of conditional probability, introducing discrete conditional probabilistic models for (multi-agent) knowledge...
Our project aims at the automatic generation of multilingual text for product maintenance and documentation from a structured knowledge representation formalized by means of plans...
This paper proposes a framework for modeling and controlling systems described by interdependent physical laws, logic rules, and operating constraints, denoted as mixed logical dy...
In this paper, we propose a method for automated web service composition by applying Linear Logic (LL) theorem proving. We distinguish value-added web services and core service by ...