Mental Models of Ambient Systems: A Modular Research Framework

  • Felix Schmitt
  • Jörg Cassens
  • Martin Christof Kindsmüller
  • Michael Herczeg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6967)


This paper outlines our current research program in the fields of ambient intelligence and context-aware computing and the tools we are building to accomplish this research program. From a discussion of our conception of mental models in the domain of ambient context-aware computer systems we derive hypotheses which we intend to test empirically. A modular framework for implementing and assessing situation awareness in humans and computers is introduced. We describe the framework’s architecture and illustrate its suitability for its intended purpose. Finally, we present an outline of our next steps towards real world application systems for our research.


Context awareness ambient intelligence mental models 


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  1. 1.
    Weiser, M.: The Computer for the Twenty-First Century. Scientific American 265, 94–100 (1991)CrossRefGoogle Scholar
  2. 2.
    Johnson-Laird, P.N.: Mental Models: Towards a Cognitive Science of Language, Inference, and Consciousness. Harvard University Press, Cambridge (1983)Google Scholar
  3. 3.
    Craik, K.J.W.: Theory of the human operator in control systems. I. The operator as an engineerig system. British Journal of Psychology 38, 56–61 (1947)Google Scholar
  4. 4.
    Endsley, M.R., Bolté, B., Jones, D.G.: Designing for Situation Awareness. Taylor & Francis, London (2003)CrossRefGoogle Scholar
  5. 5.
    Baddeley, A.D.: The episodic buffer. A new component of working memory? Trends in Cognitive Sciences 4(11), 418–423 (2000)CrossRefGoogle Scholar
  6. 6.
    Van Dijk, T.A., Kintsch, W.: Strategies of discourse comprehension. Academic Press, New York (1983)Google Scholar
  7. 7.
    Gentner, D., Stevens, A.L.: Mental Models. Lawrence Erlbaum Associates, Hillsdale (1983)Google Scholar
  8. 8.
    Wilson, J.R., Rutherford, A.: Mental models: theory and application in human factors. Human Factors 31(6), 617–634 (1989)Google Scholar
  9. 9.
    Norman, D.A.: Some Observations on Mental Models. In: Gentner, D., Stevens, A.L. (eds.) Mental Models, pp. 7–14. Lawrence Erlbaum Associates, Hillsdale (1983)Google Scholar
  10. 10.
    Kindsmüller, M.C.: Trend-Literacy. In: Zur Interpretation von Kurvendarstellungen in der Prozessführung. Shaker Verlag, Aachen (2006)Google Scholar
  11. 11.
    Rouse, W.B., Morris, N.: On looking into the black box: Prospects and limits in the search for mental models. Psychological Bulletin 100(3), 349–363 (1986)CrossRefGoogle Scholar
  12. 12.
    Turner, R.: Context-mediated behavior for intelligent agents. International Journal of Human-Computer Studies 48(3), 307–330 (1998)CrossRefGoogle Scholar
  13. 13.
    Halliday, M.A.K., Hasan, R.: Language, Context, and Text: Aspects of Language in a Social-semiotic perspective. Deakin University, Victoria (1985)Google Scholar
  14. 14.
    Schmitt, F., Cassens, J., Kindsmüller, M.C., Herczeg, M.: Mental Models of Disappearing Systems: Challenges for a Better Understanding. In: Cassens, J., Kofod-Petersen, A., Zacarias, M., Wegener, R. (eds.) Proceedings of the Sixth International Workshop on Modelling and Reasoning in Context, Lisbon, (2010)Google Scholar
  15. 15.
    Fogarty, J., Hudson, S.E., Lai, J.: Examining the robustness of sensor-based statistical models of human interruptibility. In: Dykstra-Erickson, E., Tscheligi, M. (eds.) CHI 2004: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 207–214. ACM, New York (2004)CrossRefGoogle Scholar
  16. 16.
    Hudson, S.E., Fogarty, J., Atkeson, C.G., Avrahami, D., Forlizzi, J., Kiesler, S., Lee, J.C., Yang, J.: Predicting Human Interruptibility with Sensors: A Wizard of Oz Feasibility Study. In: Cockton, G., Korhonen, P. (eds.) CHI 2003: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 257–264. ACM, New York (2003)Google Scholar
  17. 17.
    Ruge, L.: Koordinierung von Inferenz- und Lernprozessen für Pervasive-Computing-Anwendungen. Diploma thesis, University of Lübeck (2010)Google Scholar
  18. 18.
    Sirin, E., Parsia, B.: Pellet: An OWL DL reasoner. In: Haarslev, V., Möller, R. (eds.) 2004 International Workshop on Description Logics, pp. 212–213 (2004)Google Scholar
  19. 19.
    Aamodt, A., Plaza, E.: Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. AI Communications 7(1), 39–59 (1994)Google Scholar
  20. 20.
    Chen, H.: An Intelligent Broker Architecture for Pervasive Context-Aware Systems. PhD thesis, University of Maryland, Baltimore County (2004)Google Scholar
  21. 21.
    Chen, H., Finin, T., Joshi, A.: The soupa ontology for pervasive computing. In: Calisti, M., Walliser, M., Brantschen, S., Herbstritt, M., Tamma, V., Cranefield, S., Finin, T., Willmott, S. (eds.) Ontologies for Agents: Theory and Experiences. Whitestein Series in Software Agent Technologies and Autonomic Computing, pp. 233–258. Birkhäuser, Basel (2005)CrossRefGoogle Scholar
  22. 22.
    Ejigu, D., Scuturici, M., Brunie, L.: CoCA: A Collaborative Context-Aware Service Platform for Pervasive Computing. In: Latifi, S. (ed.) ITNG 2007: Proceedings of the International Conference on Information Technology, pp. 297–302. IEEE Computer Society, Washington, DC (2007)Google Scholar
  23. 23.
    Stevenson, G., Knox, S., Dobson, S., Nixon, P.: Ontonym: a collection of upper ontologies for developing pervasive systems. In: Gomez-Perez, J. (ed.) CIAO 2009: Proceedings of the 1st Workshop on Context, Information and Ontologies, pp. 1–8. ACM, New York (2009)Google Scholar
  24. 24.
    Plaza, E., Ontañón, S.: Ensemble Case-Based Reasoning: Collaboration Policies for Multiagent Cooperative CBR. In: Aha, D.W., Watson, I. (eds.) ICCBR 2001. LNCS (LNAI), vol. 2080, pp. 437–451. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  25. 25.
    Jagannathan, V., Dodhiawala, R., Baum, L.S. (eds.): Blackboard Architectures and Applications. Academic Press, Orlando (1989)zbMATHGoogle Scholar
  26. 26.
    Scheele, B., Groeben, N.: Die Heidelberger Struktur-Lege-Technik (SLT). Eine Dialog-Konsens-Methode zur Erhebung subjektiver Theorien mittlerer Reichweite. Beltz, Weinheim (1984)Google Scholar
  27. 27.
    Novak, J.D., Cañas, A.J.: The theory underlying concept maps and how to construct and use them. Tech. rep., Florida Institute for Human and Machine Cognition, IHMC (2008)Google Scholar
  28. 28.
    Norman, D.A., Draper, S.W.: User Centered System Design: New Perspectives on Human-Computer Interaction. Lawrence Erlbaum, Hillsdale (1986)Google Scholar
  29. 29.
    Palmer, S.R., Felsing, J.M.: A Practical Guide to Feature-Driven Development. Prentice Hall, Upper Saddle River (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Felix Schmitt
    • 1
  • Jörg Cassens
    • 1
  • Martin Christof Kindsmüller
    • 1
  • Michael Herczeg
    • 1
  1. 1.Institute for Multimedia and Interactive SystemsLübeckGermany

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