This paper introduces a mechanism for computing approximations of Dominance-Based Rough Sets (DBRS) by bit-vector encodings. DBRS was introduced by Greco et al. as an extension of Pawlak’s classical rough sets theory by using dominance relations in place of equivalence relations for approximating sets of preference ordered decision classes. Our formulation of dominance-based approximation space...

Incremental induction of decision rules within the dominance-based rough set approach to the multicriteria and multiattribute classification is discussed. We introduce an algorithm, called Glance, that incrementally induces a set of all rules from examples. We experimentally evaluate it and compare with two other algorithms, previously proposed for this kind of classification problem.

• On Irreducible Descriptive Sets of Attributes for Information Systems Mikhail Moshkov, Andrzej Skowron, Zbigniew Suraj • Dominance-Based Rough Set Approach and Bipolar Abstract Rough Approximation Spaces Salvatore Greco, Benedetto Matarazzo, Roman Słowinski • Paraconsistent Logic Programs with FourValued Rough Sets Jan Małuszynski, Andrzej Szałas, Aida Vitória • An Equivalent Definition of Ro...

Induction of decision rules within the dominance-based rough set approach to the multiple-criteria sorting decision problem is discussed in this paper. We introduce an algorithm called DOMLEM that induces a minimal set of generalized decision rules consistent with the dominance principle. An extension of this algorithm for a variable consistency model of dominance based rough set approach is al...

Knowledge-intensive CBR assumes that cases are enriched with general domain knowledge. In CREEK, there is a very strong coupling between cases and general domain knowledge, in that cases are embedded within a general domain model. This increases the knowledge-intensiveness of the cases themselves. A knowledge-intensive CBR method calls for powerful knowledge acquisition and modeling techniques,...

Abs t rac t . This paper presents our approach for knowledge acquisition from multiple experts. In order to build a cooperative KBS, representing the knowledge of several experts and intended to multiple users inside an organization, we propose a model of cognitive agent for guiding the process of knowledge acquisition. This model of agent can serve as a basis for specifying the future KBS to b...

Customers of electronic shops find more and more support for the search and selection of products in the sales systems. Unfortunately, most of the shops do not provide additional support with parameterizable or configurable products. Such products could be further customized. One of the major problems most customization techniques suffer from is that they require large knowledge acquisition eff...

In this paper, we give a survey on the AI-field Configuration. Because configuration of software-intensive systems is currently seen as a main challenge for knowledge-based configuration, this topic is emphasized. Main challenges related to this topic are next to others: softwareintensive applications, combining of configuration, modeling and evolution of software components, integration of kno...

We argue for the separation of object and reflective problem solving levels and a selfrepresentation that is distinct from the object-level because it is selective, specialised and knowledge oriented, i.e., it is a knowledge-level model congruent with the KADS conceptual model of the object system. As an example we describe a conceptual model for competence assessment and improvement in Office ...

The management of the integrity of intelligent systems relies on techniques to integrate the components and to manage the integrity of the knowledge-based systems components. A unified methodology integrates knowledge-based systems components with database components. Constraints are used to manage the integrity of knowledge. One class of knowledge constraints protect the integrity of knowledge...