Movatterモバイル変換


[0]ホーム

URL:


Skip to main content

Advertisement

Springer Nature Link
Log in

A Decision Case-Based System, That Reasons in Uncertainty Conditions

  • Conference paper
  • First Online:

Part of the book series:Lecture Notes in Computer Science ((LNAI,volume 2504))

Included in the following conference series:

  • 587Accesses

Abstract

Generally, most Decision Systems do not consider the uncertainty that might be present in knowledge. On many occasions, this leads to proposed solutions that are sometimes inconsistent with the expected results.

Case-Based Reasoning is one of the techniques of Artificial Intelligence used in the solution of decision-making problems. Consequently, Case-Based Systems, must consider imperfection in the available knowledge about the world.

In this paper, we present a model to make case-based decisions under uncertainty conditions. The model uses Decision Trees and Rough Set Theory to assure an efficient access and an adequate retrieval of cases.

This is a preview of subscription content,log in via an institution to check access.

Access this chapter

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Baldwin, J.F., Ribliro R.: Fuzzy reasoning by call for decision support systems. Int. Journal of uncertainty, fuzziness and knowledge-based systems, vol. 2, no 1, pages 11–24, 1994.

    Article  Google Scholar 

  2. Chen, S-J., Hwang C-L.: Fuzzy Multiple Attribute Decision Making, Methods and Applications, Springer Verlag, 1992.

    Google Scholar 

  3. Churn-Jung L.: An Overview of Rough Set Semantics for Modal and Quantifier Logic. Journal of Uncertainty, Fuzziness and Knowledge-Based Systems Vol. 8, No. 1, pages 93–118, 2000.

    MATH  Google Scholar 

  4. Gutiérrez, I., Bello, R.: La Problemática de la Incertidumbre en los Sistemas Basados en Casos. Revista de Ingeniería de la Universidad de Antioquia, 1998.

    Google Scholar 

  5. Gutiérrez, I., Bello, R., Díaz de Villegas, A. Tellería, A.: Una Métrica de Similaridad Probabilista para el Módulo de Recuperación de un Sistema Basado en Casos. Proceeding del 7mo Congreso de Nuevas Tecnologías y Aplicaciones Informáticas. La Habana, 2000.

    Google Scholar 

  6. Gutiérrez I., Bello, R.: Determinación y Manejo de la Incertidumbre en un sistema Basado en Casos. Proceedings of the 7th Joint International Iberoamerican Conference. Conference on Artificial Intelligence, 15th Brazilian Conference on Artificial Intelligence Iberamia-SBIA 2000, 2000.

    Google Scholar 

  7. Gutiérrez, I., Bello, R.: URS, Uncertainty Reasoning System. Revista de Ingeniería de la Corporación Universitaria de Ibagué, Colombia, 2002.

    Google Scholar 

  8. Merz, C. J., Murphy, P.M.: UCI Repository of Machine Learning Databases. Irvine, CA: University of California Irvine, Department of Informatics and Computer Science, 1996.

    Google Scholar 

  9. Myllymaki. P., Tirri, H.: Massively parallel case-based reasoning with probabilistic similarity metrics. In K-D. Althoff, K. Richter, and S. Wess, editors, Proceedings of the First European Workshop on Case-Based Reasoning, Kaiserslautern pages 48–53, 1993.

    Google Scholar 

  10. Parsons, S.: Current Approaches to handling Imperfect Information in Data and Knowledge Bases. IEEE Transactions on Knowledge and Data Engineering, Vol 8, No 3, 1996.

    Google Scholar 

  11. Pawlak, Z.: Vagueness and Uncertainty: a Rough Set Perspective. Computational Intelligence, Vol. 11, No 2., 1995.

    Google Scholar 

  12. Pawlak, Z.: Rough Sets: Present State and Perspectives. In: Proceedings of the Sixth International Conference “Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU’ 96)” [1], pages 1137–1146, 1996.

    Google Scholar 

  13. Pearl, J.: Probabilistic Reasoning in Intelligent Systems. Palo Alto: Morgan Kaufmann, 1988.

    Google Scholar 

  14. Sankar, K., Skowron, P.: Rough Fuzzy Hybridization: A New Trend in decision-Making. Springer, Singapore, 1999.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, Universidad Central de Las Villas, Carretera a Camajuaní km 5.5, Santa Clara, Cuba

    Iliana Gutiérrez Martínez & Rafael E. Bello Pérez

Authors
  1. Iliana Gutiérrez Martínez

    You can also search for this author inPubMed Google Scholar

  2. Rafael E. Bello Pérez

    You can also search for this author inPubMed Google Scholar

Editor information

Editors and Affiliations

  1. Departament d’Enginyeria i Ciència dels Computadors, Universitat Jaume 1, Campus de Riu Sec, 12071, Castellón, Spain

    M. Teresa Escrig  & Francisco Toledo  & 

  2. Computer Science Department, Universitat Ramon Llull, Passeig Bonanova, 8, 08022, Barcelona, Catalunya, Spain

    Elisabet Golobardes

Rights and permissions

Copyright information

© 2002 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Martínez, I.G., Pérez, R.E.B. (2002). A Decision Case-Based System, That Reasons in Uncertainty Conditions. In: Escrig, M.T., Toledo, F., Golobardes, E. (eds) Topics in Artificial Intelligence. CCIA 2002. Lecture Notes in Computer Science(), vol 2504. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36079-4_5

Download citation

Publish with us


[8]ページ先頭

©2009-2025 Movatter.jp