Overview of Knowledge Formalization with XTT2 Rules

  • Grzegorz J. Nalepa
  • Antoni Ligęza
  • Krzysztof Kaczor
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6826)

Abstract

The paper discusses a new formalized knowledge representation for rule-based systems called XTT2. This hybrid knowledge representation combines decision diagrams with extended decision tables. A single decision table contains a set of rules of similar structure operating within a common context. The structure of XTT2 constitutes a hierarchical knowledge representation consisting of lower level knowledge components, where specification is provided by a set of rules working in the same context, and at the higher level, where the decision diagram defines the overall structure of the knowledge base. This model has a concise formalization which opens up possibility for rigorous design and verification. The focus of the paper is on the presentation of the formal aspects of the approach starting from an initial logical specification.

Keywords

Knowledge Base Knowledge Representation Atomic Formula Decision Table 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

  • Grzegorz J. Nalepa
    • 1
  • Antoni Ligęza
    • 1
  • Krzysztof Kaczor
    • 1
  1. 1.AGH University of Science and TechnologyKrakówPoland

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