When there is a need to understand the data stored in a database, one of the main requirements is being able to extract knowledge in the form of rules. Classification strategies allow extracting rules almost naturally. In this paper, the…

MoKEx (Mobile Knowledge Experience) is an international project in cooperation with universities and industrial partners. The project focuses on didactical, organizational and technical problems with regard to blended learning and knowledge management scenarios. In a project-based learning approach students of…

The software industry blames universities for their graduates lacking necessary skills, meaning that just the possession of knowledge does not necessarily imply the competent performance required by the profession.
Professional maturity in software engineering is one of software industry’s major…

In this work two declarative approaches based on the BDI theory are studied, an agent programming language 3APL and an agent architecture that uses defeasible argumentation for knowledge representation and reasoning. Based on that study and considering that in 3APL…

This article presents the confluence of two general ideas: Defeasible Logic Programming (DeLP, an argumentation based formalism for representing knowledge and reasoning) and Abduction in logic. In first place, we introduce a framework that formally states the problem of doing…

When using tableaux algorithms to reason about Description Logics (DLs), new information is inferred from the models considered while trying to achieve knowledge satisfiability. By focusing the ontology change problem, we consider an environment where DLs are the logical formalization…

This study investigates an approach of knowledge discovery and data mining in insufficient databases. An application of Computational Taxonomy analysis demonstrates that the approach is effective in such a data mining process. The approach is characterized by the use ot…

In this paper, the two-dimensional strip packing problem with 3-stage level patterns is tackled using genetic algorithms (GAs). We evaluate the usefulness of a greedy seeding procedure for creating the initial population, incorporating problem knowledge. This is motivated by the…

In this paper, we build on previous work on Belief Revision operators based on the use of logic programming with Answer Set semantics as a representation language. We present a set of postulates for Answer Set Revision with respect to…

Argumentative formalisms have been widely recognized as knowledge representation and reasoning tools able to deal with incomplete and potentially contradictory informa- tion. All such formalisms are computationally demanding. Hence, optimizing argumen- tative systems has been approached from di erent views.