56 research outputs found

    A comparison of languages which operationalise and formalise {KADS} models of expertise

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    In the field of Knowledge Engineering, dissatisfaction with the rapid-prototyping approach has led to a number of more principled methodologies for the construction of knowledge-based systems. Instead of immediately implementing the gathered and interpreted knowledge in a given implementation formalism according to the rapid-prototyping approach, many such methodologies centre around the notion of a conceptual model: an abstract, implementation independent description of the relevant problem solving expertise. A conceptual model should describe the task which is solved by the system and the knowledge which is required by it. Although such conceptual models have often been formulated in an informal way, recent years have seen the advent of formal and operational languages to describe such conceptual models more precisely, and operationally as a means for model evaluation. In this paper, we study a number of such formal and operational languages for specifying conceptual models. In order to enable a meaningful comparison of such languages, we focus on languages which are all aimed at the same underlying conceptual model, namely that from the KADS method for building KBS. We describe eight formal languages for KADS models of expertise, and compare these languages with respect to their modelling primitives, their semantics, their implementations and their applications. Future research issues in the area of formal and operational specification languages for KBS are identified as the result of studying these languages. The paper also contains an extensive bibliography of research in this area

    Graphical and formal knowledge specification with KARL

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    A model of expertise in KARL

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    Cokace: A Centaur-based environment for CommonKADS Conceptual Modelling Language

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    International audienceIn order to help the knowledge engineer during knowledge modelling phase, we developed an environment for the conceptual modelling language CML offered by the CommonKADS methodology. This environment, called Cokace, was designed using Centaur, a programming environment generator, that was usually exploited for building environments dedicated to software engineering languages. Thanks to Centaur, Cokace provides the knowledge engineer with structured edition, static validation and dynamic interpretation of CML expertise models. Cokace allows the knowledge engineer to simulate a reasoning on CML expertise models, and enables verification and evaluation of such expertise models before implementation of the final knowledge-based system. This work illustrates an example of the benefits knowledge engineering can get from well established techniques and tools available in software engineering
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