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Article type: Research Article
Authors: Reinders, Martin; | Vinkhuyzen, Erik | Voß, Angi | Akkermans, Hans | Balder, John | Bartsch-Spörl, Brigitte | Bredeweg, Bert | Drouven, Uwe | van Harmelen, Frank | Karbach, Werner | Karssen, Zeger | Schreiber, Guus | Wielinga, Bob
Affiliations: Netherlands Energy Research Foundation ECN | SWI, University of Amsterdam | National German Research Centre for Computer Science GMD | BSR Consulting
Note: [] Conctact: Martin Reinders, ECN, P.G. Box 1, 1755 ZG Petten, The Netherlands. reinders@ecn.nl
Abstract: In this paper we develop a conceptual modelling framework for knowledge-level reflection (KLR), i.e., the modelling of tasks that require a self-representation of a knowledge system's own object-level problem solving tasks. This framework builds upon the KADS methodology for knowledge acquisition and design of knowledge systems [Hayward et al., 1987, Wielinga et al., 1991]. We argue for the separation of object and reflective problem solving levels and a self-representation 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 Plan, a configuration system for office space allocation. A broad comparison with notions of reflection in logic and computational reflection clarifies the distinctiveness of our notion of knowledge level reflection and investigates some of the architectural options that are open for its realisation in knowledge systems.
DOI: 10.3233/AIC-1991-42-305
Journal: AI Communications, vol. 4, no. 2-3, pp. 74-87, 1991
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