Constrained Sums of Information Systems

  • Andrzej Skowron
  • Jarosław Stepaniuk
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3066)


We study properties of infomorphisms between information systems. In particular, we interpret infomorphisms between information systems in terms of sums with constraints (constrained sums, for short) that are some operations on information systems. Applications of approximation spaces, used in rough set theory, to study properties of infomorphisms are included.


Information System Multiagent System Decision Table Approximation Space Constraint Relation 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Barwise, J., Seligman, J.: Information Flow: The Logic of Distributed Systems, Cambridge University Press Tracts in Theoretical Computer Science 44 (1997)Google Scholar
  2. 2.
    Garcia-Molina, H., Ullman, J.D., Widom, J.D.: Database Systems: The Complete Book. Prentice Hall, Upper Saddle River (2002)Google Scholar
  3. 3.
    Kloesgen, W., Żytkow, J. (eds.): Handbook of Knowledge Discovery and Data Mining. Oxford University Press, Oxford (2002)zbMATHGoogle Scholar
  4. 4.
    Łukasiewicz, J.: Die logischen grundlagen der wahrscheinilchkeitsrechnung, Kraków 1913. In: Borkowski, L. (ed.) Jan Łukasiewicz - Selected Works, North Holland Publishing Company, Polish Scientific Publishers, Amstardam, London, Warsaw (1970)Google Scholar
  5. 5.
    Pawlak, Z.: Rough Sets. Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers, Dordrecht (1991)zbMATHGoogle Scholar
  6. 6.
    Pal, S.K., Polkowski, L., Skowron, A. (eds.): Rough-Neural Computing: Techniques for Computing with Words. Springer, Berlin (2004)zbMATHGoogle Scholar
  7. 7.
    Polkowski, L., Skowron, A.: Towards adaptive calculus of granules. In: [14], pp. 201–227Google Scholar
  8. 8.
    Skowron, A., Stepaniuk, J.: Tolerance Approximation Spaces. Fundamenta Informaticae 27, 245–253 (1996)zbMATHMathSciNetGoogle Scholar
  9. 9.
    Skowron, A., Stepaniuk, J.: Information Granules: Towards Foundations of Granular Computing. International Journal of Intelligent Systems 16(1), 57–86 (2001)zbMATHCrossRefGoogle Scholar
  10. 10.
    Skowron, A., Stepaniuk, J.: Information Granules and Rough-Neuro Computing. In: [6], pp. 43–84Google Scholar
  11. 11.
    Skowron, A., Stepaniuk, J., Peters, J.F.: Rough Sets and Infomorphisms: Towards Approximation of Relations in Distributed Environments. Fundamenta Informaticae 54(1-2), 263–277 (2003)zbMATHMathSciNetGoogle Scholar
  12. 12.
    Stepaniuk, J.: Knowledge Discovery by Application of Rough Set Models. In: Polkowski, L., Tsumoto, S., Lin, T.Y. (eds.) Rough Set Methods and Applications. New Developments in Knowledge Discovery in Information Systems, pp. 137–233. Physica-Verlag, Heidelberg (2000)Google Scholar
  13. 13.
    Zadeh, L.A.: Toward a theory of fuzzy information granulation and its certainty in human reasoning and fuzzy logic. Fuzzy Sets and Systems 90, 111–127 (1997)zbMATHCrossRefMathSciNetGoogle Scholar
  14. 14.
    Zadeh, L.A., Kacprzyk, J. (eds.): Computing with Words in Information/Intelligent Systems, vol. 1-2. Physica-Verlag, Heidelberg (1999)Google Scholar
  15. 15.
    Zadeh, L.A.: A new direction in AI: Toward a computational theory of perceptions. AI Magazine 22(1), 73–84 (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Andrzej Skowron
    • 1
  • Jarosław Stepaniuk
    • 2
  1. 1.Institute of MathematicsWarsaw UniversityWarsawPoland
  2. 2.Department of Computer ScienceBiałystok University of TechnologyBiałystokPoland

Personalised recommendations