Partial Orders as a Basis for KBS Semantics

  • Simon P. H. Morgan
  • John G. Gammack


Partial orders are a mathematical construct currently used in denotational semantics. This construct has several properties which make it more generally applicable to knowledge-based systems (KBS) design, and in this paper we consider the role of partial orders in describing the meanings of data states in knowledge based systems. Partial orders allow formal representation of the state of information and inferences made about the external world, as stored in dynamically generated data structures of the KBS. A partial order can be augmented with a single representation of the reasoning strategies of a KBS, which includes representation of how a KBS might adapt reasoning strategies depending on the information available to it. This gives a common theoretical framework for KBS methods.


Partial Order External World Operational Semantic Declarative Knowledge Denotational Semantic 
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. Gammack, J.G. Battle, S.A. and Stephens, R.A. (1989) A knowledge acquisition and representation scheme for constraint-based and parallel systems. Proc. IEEE conference on Systems Man and Cybernetics. Cambridge, MA. vol. III, p1030–1035.CrossRefGoogle Scholar
  2. Lazowska, E.D., Zahorjan, J., Scott-Graham, G. and Sevcik, K.C. (1984) Quantitative System Performance., Prentice Hall, New Jersey.Google Scholar
  3. Leier, W. (1988) Constraint Programming Languages, Addison-Wesley.Google Scholar
  4. Patel, V.L. and Groen, G.J. (1986) Knowledge based solution strategies in medical reasoning. Cognitive Science, 10, 91–116.CrossRefGoogle Scholar
  5. Pearl, J. (1985) How to do with probabilities what people say you can’t. C.R. Weisbin (Ed). Artificial Intelligence Applications: The engineering of Knowledge-Based Systems North-Holland 1985.Google Scholar
  6. Pitrat, J. (1984) An intelligent program can and must use declarative knowledge efficiently. In Elithorn, A. and Banerji, R. (Eds.) Artificial and Human Intelligence, Elsevier, North-Holland.Google Scholar
  7. Scott, D.S. (1976) Data types as lattices. Society of Industrial and Applied Mathematics(SIAM) journal of Computing vol 5, no 3.Google Scholar

Copyright information

© Springer-Verlag New York, Inc. 1990

Authors and Affiliations

  • Simon P. H. Morgan
    • 1
  • John G. Gammack
    • 2
  1. 1.Department of Computer ScienceUniversity of ExeterExeter, DevonUK
  2. 2.Bristol Business SchoolFrenchay BristolEngland

Personalised recommendations