Advertisement

A Generic and Modular System Architecture for Trustworthy, Autonomous Applications

  • George Brancovici
  • Christian Müller-Schloer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4610)

Abstract

We propose a generic architecture to facilitate the systematic design of autonomous, adaptive and safe applications. We specify generic modules including a trustworthiness enforcement layer dedicated to ensure the system’s functional stability as seen by the human owner. Instead of building a monolithic system, we encourage modularization based on the cognitive function of the components. A key premise is that domain knowledge is explicitly specified as a parameter of each application, with the side effect of enabling seamless integration with other remote autonomous or infrastructure applications. The design choices we have made are exemplified on a demonstrative travel management application.

Keywords

Domain Knowledge Inference Engine Abductive Reasoning Intelligent Application Inductive Reasoner 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Guizzardi, G., Wagner, G., Guarino, N., van Sinderen, M.: An Ontologically Well-Founded Profile for UML Conceptual Models. In: Persson, A., Stirna, J. (eds.) CAiSE 2004. LNCS, vol. 3084, Springer, Heidelberg (2004)Google Scholar
  2. 2.
    Cranefield, S., Purvis, M.: UML as an ontology modelling language. In: Proceedings of the Workshop on Intelligent Information Integration. In: 16th International Joint Conference on Artificial Intelligence (IJCAI) (1999)Google Scholar
  3. 3.
    Cranefield, S.: UML and the Semantic Web. In: Proceedings of the International Semantic Web Working Symposium (SWWS) (2001)Google Scholar
  4. 4.
    Degen, W., Heller, B., Herre, H., Smith, B.: GOL: A General Ontological Language. In: Proceedings of the International Conference on Formal Ontology in Information Systems (FOIS) (2001)Google Scholar
  5. 5.
    Gorman, J.: UML for Java Developers, Model Constraints & the Object Constraint Language, http://www.parlezuml.com
  6. 6.
    d’Avila Garcez, A., Russo, A., Nuseibeh, B., Kramer, J.: Combining Abductive Reasoning and Inductive Learning to Evolve Requirements Specifications. In: IEEE Proceedings - Software (2003)Google Scholar
  7. 7.
    Mili, A., Jiang, G., Cukic, B., Liu, Y., Ben Ayed, R.: Towards the Verification and Validation of Online Learning Systems: General Framework and Applications. In: Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS) (2004)Google Scholar
  8. 8.
    Watkins, A., Berndt, D., Aebischer, B., Fisher, J., Johnson, L.: Breeding Software Test Cases for Complex Systems. In: Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS) (2004)Google Scholar
  9. 9.
    Ilghami, O.: Documentation for JSHOP2. In: Technical Report, CS-TR-4694, Department of Computer Science, University of Maryland (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • George Brancovici
    • 1
  • Christian Müller-Schloer
    • 1
  1. 1.University of Hannover, Institute of Systems Engineering, System and Computer Architecture, Appelstr. 4, 30167 HannoverGermany

Personalised recommendations