Advertisement

An Integrated Agent Model Addressing Situation Awareness and Functional State in Decision Making

  • Mark Hoogendoorn
  • Rianne van Lambalgen
  • Jan Treur
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7047)

Abstract

In this paper, an integrated agent model is introduced addressing mutually interacting Situation Awareness and Functional State dynamics in decision making. This shows how a human’s functional state, more specific a human’s exhaustion and power, can influence a human’s situation awareness, and in turn the decision making. The model is illustrated by a number of simulation scenarios.

Keywords

Situation awareness functional state agent model 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Cnossen, F., Rothengatter, T., Meijman, T.: Strategic changes in task performance in simulated car driving as an adaptive response to task demands. Transportation Research Part F 3, 123–140 (2000)CrossRefGoogle Scholar
  2. 2.
    Endsley, M.R.: Toward a theory of Situation Awareness in dynamic systems. Human Factors 37, 32–64 (1995)CrossRefGoogle Scholar
  3. 3.
    Hockey, G.R.J.: Compensatory control in the regulation of human performance under stress and high workload: a cognitive-energetical framework. Biological Psychology 45, 73–93 (1997)CrossRefGoogle Scholar
  4. 4.
    Hockey, G.R.J.: Operator functional state as a framework for the assessment of performance degradation. In: Hockey, G.R.J., et al. (eds.) Operator Functional State. IOS Press (2003)Google Scholar
  5. 5.
    Hoogendoorn, M., van Lambalgen, R., Treur, J.: Modeling Situation Awareness in Human-Like Agents using Mental Models. In: Walsh, T. (ed.) Proc. of the Twenty-Second Intern. Joint Conference on Artificial Intelligence, IJCAI 2011, pp. 1697–1704 (2011)Google Scholar
  6. 6.
    Hoogendoorn, M., Merk, R.J., Treur, J.: An Agent Model for Decision Making Based upon Experiences Applied in the Domain of Fighter Pilots. In: Huang, X.J., et al. (eds.) Proceedings of the 10th IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2010, pp. 101–108. IEEE Computer Society Press (2010)Google Scholar
  7. 7.
    Klein, M.C.A., van Lambalgen, R., Treur, J.: An Agent Model for Analysis of Human Performance Quality. In: Huang, X.J., et al. (eds.) Proceedings of the 10th IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2010, pp. 181–188. IEEE Computer Society Press (2010)Google Scholar
  8. 8.
    Matthews, G., Desmond, P.A.: Task-induced fatigue states and simulated driving performance. The Quarterly Journal of Exp. Psy. 55A, 659–686 (2002)CrossRefGoogle Scholar
  9. 9.
    Maule, A.J., Hockey, G.R.J., Bdzola, L.: Effects of time-pressure on decision-making under uncertainty: changes in affective state and information processing strategy. Acta Psychologica 104, 283–301 (2000)CrossRefGoogle Scholar
  10. 10.
    Recarte, M.A., Nunes, L.M.: Mental workload while driving: effects on visual search, discrimination and decision making. Journal of Exp. Psy. Applied 9, 119–137 (2003)CrossRefGoogle Scholar
  11. 11.
    Venables, L., Fairclough, S.H.: The influence of performance feedback on goal-setting and mental effort regulation. Motiv. Emot. 33, 63–74 (2009)CrossRefGoogle Scholar
  12. 12.
    Wickens, C.D., Hollands, J.G.: Engineering Psychology and Human Performance. Prentice Hall, Upper Saddle River (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Mark Hoogendoorn
    • 1
  • Rianne van Lambalgen
    • 1
  • Jan Treur
    • 1
  1. 1.Agent Systems Research GroupVU University AmsterdamAmsterdamThe Netherlands

Personalised recommendations