Automatic analysis, verification and synthesis of rule-based real-time decision making systems with machine learning assistance

  • Basilis Boutsinas
  • Stergios Papadimitriou
  • Georgios Pavlides
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1181)


Machine learning techniques suggest new approaches to the problems encountered in Systems Engineering. This paper presents a framework for the analysis and verification of a class of rule-based realtime decision making systems. This framework is based on the technique of Explanation-based generalization that is used to generalize rule-based programs in order to support both their reuse, analysis and verification. The latter task, in this class of systems, is in general undecidable and in the case where all the variables are restricted to take values in finite domains it is PSPACE-hard. The most important topic addressed in this work is the reuse of existing components in order to support both the evaluation of the worst-case execution time and the automatic verification of the real-time decision making system. The proposed methodology seems to be quite efficient in practical cases.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Basilis Boutsinas
    • 1
  • Stergios Papadimitriou
    • 1
  • Georgios Pavlides
    • 1
  1. 1.Department of Computer Engineering & InformaticsUniversity of PatrasRioGreece

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