Visual Design of Drools Rule Bases Using the XTT2 Method

  • Krzysztof Kaczor
  • Grzegorz Jacek Nalepa
  • Łukasz Łysik
  • Krzysztof Kluza
Part of the Studies in Computational Intelligence book series (SCI, volume 381)


Drools is one of the most popular expert system frameworks. It uses rules in several formats as knowledge representation. However, Drools has several limitations. It does not support visual modeling of rules. Moreover, it does not assure quality of the knowledge base. In this paper an alternative way of knowledge base designing for Drools is proposed. The method extends the Drools design process by using the XTT2 rule representation and the HQEd visual rule editor. To deal with the differences between the XTT2 and Drools representations, the Drools Export Plugin for HQEd has been implemented. The proposed approach overcomes limitations of the Drools design methodology. Furthermore, it provides a visual rule design editor for Drools and supports formal verification of the model using an optional module.


Knowledge Base Rule Base Decision Table Visual Design Inference Process 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Krzysztof Kaczor
    • 1
  • Grzegorz Jacek Nalepa
    • 1
  • Łukasz Łysik
    • 1
  • Krzysztof Kluza
    • 1
  1. 1.AGH University of Science and TechnologyKrakowPoland

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