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Structured Methods of Representation of the Knowledge

  • Francisco João Pinto
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 801)

Abstract

This paper describes same of the structured methods of representation of the knowledge that we introduced as an alternative to the procedures of representation more formal. After a brief mention to the essential characteristics that we have to take into account to any structured method of representation of the knowledge, classified into declarative methods and procedural methods. Declarative methods give more importance to the facts and entities of the domain that to the mechanisms of manipulation of the same. By contrary, the procedural methods, although they operate on facts and entities of the domain of speech, gives greater attention to the mechanisms of relation between entities. The declarative methods studied in this paper are the semantic network in which the knowledge is represented like a collection of joined nodes among them by means of labeled arches, the frames that can be defined as complex semantic network that treat the problem of the representation from the optics of the reasoning for likeness. Moreover, we described the formalism of the production rules, putting special attention in their structure and their form of cooperating with some declarative of representation (for example frames).

Keywords

Structured methods Representation of the knowledge Artificial intelligence 

References

  1. 1.
    Baral, C., Delgrande, J., Wotter, F.: Principles of knowledge Representation and Reasoning. kr.org. KR Inc. Accessed 22 Nov 2017Google Scholar
  2. 2.
    Bonillo, V.M., Betanzos, A.A., Canosa, M.C., Berdiñas, B.G., Rey, E.M.: Fundamentos de Inteligencia Artificial, Capítulo 4, páginas 87–93, 97 e 98, 111–115, Universidad de la Coruña-España (2000)Google Scholar
  3. 3.
    Gonzales, D.: Verification and Validation. The engineering of Knowledge-Based Systems: Theory and Practice. Prentice-Hall International (1993)Google Scholar
  4. 4.
    Hayes-Roth, F., Waterman, D., Lenat, D.: Building Expert Systems. Addison-Wesley, Reading (1983). ISBN 0-201-10686-8Google Scholar
  5. 5.
    Rolston, D.W.: Principios de inteligencia Artificial y Sistemas expertos. McGraw-Hill (1990)Google Scholar
  6. 6.
    Rich, K.: Intelligence Artificial. McGraw-Hill, New York (1994)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Engineering, Faculty of EngineeringUniversity Agostinho NetoLuandaAngola

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