Application of graph grammars to rule-based systems

  • Martin Korff
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 532)


Graph grammars can easily be considered as models for rule-based systems where solving state-space problems essentially requires searching. Since many AI problems are naturally graphical, graph grammars could narrow the usual gap between a problem and its formal specification.

In order to be able to solve such problems in practice one must reduce the effort of search. Here, for graph grammar specifications, the idea of precomputing its rules allows to prune the corresponding search-trees safely by explicitly pointing to those subtrees which are contained in others. Moreover, for some rules it becomes possible to use the information of a rule's former for to predict its later non-applicability, thus avoiding some redundant, expensive applicability tests. The example of solving a domino game based on breadth-first search demonstrates that indeed some remarkable reductions can be obtained.


Graph grammar rule-based system rule independency search-space reduction 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [Ehr 79]
    H. Ehrig: “Introduction to the Algebraic Theory of Graph Grammars” — LNCS 73, Springer Verlag, Berlin, pp. 1–69, 1979Google Scholar
  2. [EhrHa 85]
    H. Ehrig, A. Habel: “Graph Grammars with Application Conditions” — In ”The Book of L”, Springer Verlag, Berlin, pp. 87–100, 1985Google Scholar
  3. [EhrHaRo 86]
    H. Ehrig, A. Habel, B.K. Rosen: “Concurrent Transformations of Relational Structures” — Fundamenta Informatica, Vol IX (1), 1986Google Scholar
  4. [Ko 90]
    M. Korff: “Optimizations of Production Systems based on Algebraic Graph Transformations” — Technical Report 90/8, TU Berlin, 1990Google Scholar
  5. [Kre 78]
    H.-J. Kreowski: “Anwendungen der algebraischen Graphentheorie auf Konsistenz und Synchronisation in Datenbanksystemen” — Technical Report 78/15, TU Berlin, 1978Google Scholar
  6. [KreWi 83]
    H.-J. Kreowski and A. Habel: “Is Parallelism already Concurrency? Part II: Non-Sequential Processes in Graph Grammars” — LNCS 153, Springer Verlag, Berlin, pp. 360–380, 1987Google Scholar
  7. [Lö 89]
    M. Löwe: “Implementing Algebraic Specifications by Graph Transformation Systems” — Technical Report 89/26 of FB 20 at the TU Berlin, 1989Google Scholar
  8. [MoPa 87]
    D. Moldovan and F. Parisi-Presicce: “Parallelism Analysis in Rule-Based Systems Using Graph Grammars” — LNCS 291, Springer Verlag, Berlin, pp. 427–439, 1987Google Scholar
  9. [Ja 74]
    P. Jackson, Jr.: “Introduction to artificial intelligence” — Mason & Lipscomb Publishers, Inc., London, 1974Google Scholar
  10. [Ni 74]
    N. Nilson: “Principles of Artificial Intelligence” — Springer Verlag, Berlin, 1982Google Scholar
  11. [Ri 83]
    E. Rich: “Artificial Intelligence” — New York: McGraw-Hill, 1986Google Scholar
  12. [ShiTsu 84]
    Y. Shirai, J. Tsujii: “Artificial Intelligence: Concepts, Techniques and Applications” — John Wiley & Sons, 1984Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Martin Korff
    • 1
  1. 1.Computer Science DepartmentTechnical University of BerlinBerlin 10

Personalised recommendations