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Abstract

Knowledge and Intelligence have a much closed relationship. Knowledge is both the crystallization and source of intelligence. Knowledge embodies intelligence, and intelligence emerges from knowledge. Every ICAX system (Intelligent Computer Aided X, where X may mean any domain, such as education, design or manufacturing, etc.), such as ICAI (I = Instruction), ICAD (D = Design), ICAM (M = Manufacturing), etc., has its intelligence based on a content rich knowledge base. In this sense, we may have the formula: ICAX = CAX + X knowledge base. Using this formula, we have developed a methodology of generating knowledge based system automatically. The core idea is to develop a domain-oriented pseudo-natural language (PNL for short), where PNL means a normalized subset of some natural language, which can be easily parsed by computer. Each domain expert may use this language to write down his knowledge and experience. A PNL compiler then compiles ’program’s written in this PNL to form a domain knowledge base. Combined with a preexisting system shell, a prototype of the knowledge based system is automatically generated. We have applied this idea to automatic generation of ICAI and ICASE (SE = Software Engineering) systems. The following problem is how to generalize this idea. Can the development of knowledge base and system shell be done by different people or groups? Can the knowledge base be easily renewed or even become an independent commodity? Finally, we have got an answer to this problem. The commodity form of such knowledge base is knowware. In general, knowware is a commodity form of knowledge.

More precisely, knowware is a commercialized knowledge module with documentation and intellectual property, which is computer operable, but free of any built-in control mechanism, meeting some industrial standards and embeddable in software/hardware. The process of development, application and management of knowware is called knowware engineering. Three different knowware life cycle models are discussed: the furnace model, the crystallization model and the spiral model. Software/knowware co-engineering is a mixed process involving both software engineering and knowware engineering issues. It involves three parallel lines of developing system components of different types. The key issues of this process are how to guarantee the correctness and appropriateness of system composition and decomposition. The ladder principle, which is a modification of the waterfall model, and the tower principle, which is a modification of the fountain model, are proposed.

Keywords

Knowledge Base Intellectual Property Domain Expert Automatic Generation System Composition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

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    Lu, R.Q.: From Hardware to Software to Knowware: IT’s third liberation? IEEE Intelligent systems 20(2), 82–85 (2005)CrossRefGoogle Scholar
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    Lu, R.Q., Jin, Z.: Beyond Knowledge Engineering. Journal of Computer Science and Technology 21(5), 790–799 (2006)CrossRefGoogle Scholar
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    Lu, R.Q.: Towards a Software/Knowware Co-engineering. In: Lang, J., Lin, F., Wang, J. (eds.) KSEM 2006. LNCS (LNAI), vol. 4092, pp. 23–32. Springer, Heidelberg (2006)CrossRefGoogle Scholar
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    Lu, R.Q.: Knowware, Knowware Engineering and Knowware/Software Co-engineering. In: ICCS 2007, Invited Talk, Beijing, China (2007)Google Scholar
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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Ruqian Lu
    • 1
  1. 1.Academy of Mathematics and System Science, The Chinese Academy of SciencesBeijingP.R. China

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