QIL(ID:5413/qil001)

Conceptual modelling language developed at the University of Nottingham

Originally a generalpurpose language, but used largely in KADS
References:
  • Aitken, S. ; H. Reichgelt, N. Shadbolt: Representing KADS models in QIL, AI Group, University of Nottingham, Working Paper WP-006, 1992. view details
  • Aitken, S. ; O. Kühn, N. Shadbolt, F. Schmalhofer: A Conceptual Model of Hierarchical Skeletal Planning and its Formalization. In Proceedings of the 3rd KADS Meeting , Munich, March 8-9, 1993. view details
  • Fensel, Dieter and van Harmelen, Frank "A Comparison of Languages which Operationalise and Formalise KADS Models of Expertise" The Knowledge Engineering Review, 9(2), 1994. view details Abstract: 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 knowledgebased 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.


    External link: Online copy Extract: FORKADS
    FORKADS has been developed at the IBM Germany Scientific Center in Heidelberg. It was one of the first published approaches to formal KADS models.
    Contrary to the languages described so far, FORKADS aims not only at operationalizing KADS models, but also at giving formal foundations to KADS models. Furthermore, the aim is to use this language as a (or perhaps even the only) communication medium between the people responsible for knowledge acquisition and those responsible for system design. For this purpose, the main foundation of FORKADS is a first-order logical language which is extended with notions of concept heterarchies and procedural attachment. In many respects FORKADS is rooted in the LLILOG language Extract: QIL
    QIL is a language developed at the University of Nottingham. Although QIL is originally intended as a model for multi-agent systems, where multiple agents can have beliefs that evolve over time, shows how QIL can be used to describe KADS models.
    Of the languages discussed in this paper, QIL and KBSSF are the only languages that were originally designed for general knowledge-representation purposes, whereas the other languages were specifically developed to represent KADS-models. Extract: (ML)2
    (ML)2  is a language for formalizing KADS models of expertise. It was developed in the course of the ESPRIT Projects "REFLECT" and "KADS-II" and a bilateral research project of the Netherlands Energy Research Foundation ECN and the University of Amsterdam. Although a subset of (ML)2 can be operationalized to
    allow explorative prototyping it is mainly introduced as a formalization language.