The Knowledge Acquisition and Representation Language, KARL

1. Front Matter

   Pages i-xix

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2. Introduction

   • Dieter Fensel

   Pages 1-38

3. Logical-KARL

   • Dieter Fensel

   Pages 39-62

4. Procedural-KARL

   • Dieter Fensel

   Pages 63-70

5. The KARL Model of Expertise

   • Dieter Fensel

   Pages 71-131

6. The Formal Semantics of KARL

   • Dieter Fensel

   Pages 133-185

7. Conclusion

   • Dieter Fensel

   Pages 187-211

8. Back Matter

   Pages 213-238

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Within the framework of so-called second generation expert systems [62] knowledge modeling is one of the most important aspects. On the one hand, knowledge acquisition is no longer seen as a knowledge transfer process, rather it is now considered as model construction process which is typically a cyclic and error prone process. On the other hand, the distinction between knowledge and symbol level descriptions [166] resulted in various proposals for conceptual knowledge models describing knowledge in an implementation independent way. One of the most prominent examples of such a conceptual model is the KADS model of expertise which is characterized by its clear distinction of different know ledge types and by the usage of specific modeling primitives to describe these different knowledge types [185]. The semi­ formal KADS expertise model entails all the advantages and disadvantages which have been identified for semi-formal system models e.g. in the software engineering community.

• Attribut
• Syntax
• control
• expert system
• formal language
• knowledge
• knowledge engineering
• knowledge-based system
• knowledge-based systems
• language
• modeling
• semantics
• structured analysis
• testing
• validation

• University of Karlsruhe, Germany

  Dieter Fensel

• Department SWI, University of Amsterdam, Amsterdam, Netherlands

  Dieter Fensel

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