Cognitive Aspects of Higher Level Fusion

Abstract

A commander’s situation awareness is critical to his or her decision making in a crisis but the ability for a commander to form that situation awareness is often overestimated. Automated data fusion offers a means of supporting a commander’s situation awareness, with automated higher level fusion supporting the higher level functions of comprehension and projection. This chapter outlines a software-implemented psychological model that allows a machine to perform comprehension and projection, and interact with a commander.

References

  1. Block NJ (1980) Introduction: what is functionalism? Readings. In: Block NJ (ed) Philosophy of psychology, vol 1. Harvard University Press, Cambridge, MA, pp 171–184Google Scholar
  2. Broughton M, Carr O, Estival D, Taplin P, Wark S, Lambert DA. Conversing with Franco, Focal’s virtual adviser, Conversational Character Workshop, Human Factors 2002, Melbourne, Australia, 2002Google Scholar
  3. Burks AW, Goldstine HH, von Neuman J (1971) Preliminary discussion of the logical design of an electronic computing instrument. In: Bell CG, Newell A (eds) Computer structures: readings and examples. McGraw-Hill Book Company, New York, NY, pp 92–119Google Scholar
  4. Churchland PM (1988) Matter and consciousness: a contemporary introduction to the philosophy of mind, a Bradford book. MIT Press, CambridgeGoogle Scholar
  5. Dennett DC (1971) Intentional systems. In: Dennett DC (ed) Brainstorms: philosophical essays on mind and psychology. The Harvester Press Limited, Brighton, Sussex, pp 3–22Google Scholar
  6. Endsley MR (1988) Design and evaluation for situation awareness enhancement. In: Proceedings of the Human Factors Society 32nd Annual Meeting Santa Monica, CA: Human Factors Society, pp 97–101Google Scholar
  7. Endsley MR (1999) Situation awareness and human error: designing to support human performance. In: Proceedings of the High Consequence Systems Surety Conference, Albuquerque, NMGoogle Scholar
  8. Fodor JA (1987) Psychosemantics: the problem of meaning in the philosophy of mind. The MIT Press, Cambridge, MAGoogle Scholar
  9. Giompapa S, Farina A, Gini F, Graziano A, Di Stefano R (2006) A model for a human decision-maker in a command and control radar system: surveillance tracking of multiple targets. In: Proceedings of the 9th International Conference on Multisource Information fusion, Florence, ItalyGoogle Scholar
  10. Lambert DA (1999) Advisers with attitude for situation awareness. In: Proceedings of the 1999 Workshop on Defense Applications of Signal Processing, LaSalle, IL, pp. 113–118Google Scholar
  11. Lambert DA (2001) Situations for situation awareness. In: Proceedings of the 4th International Conference on Information Fusion, Montreal, QCGoogle Scholar
  12. Lambert DA (2009) A blueprint for higher level fusion systems. J Inf Fusion 10:6–24CrossRefGoogle Scholar
  13. Lambert DA (2012a) The state transition data fusion model, Ch 3. In: Blasch E, Bossé É, Lambert DA (eds) High-level information fusion management and system design. Boston, MA, Artech House, pp 33–79Google Scholar
  14. Lambert DA (2012b) Coalition approach to high-level information fusion, Ch 12. In: Blasch E, Bossé É, Lambert DA (eds) High-level information fusion management and system design. Boston, MA, Artech House, pp 251–277Google Scholar
  15. Lambert DA, Nowak C (2008) The Mephisto conceptual framework. DSTO technical report TR-2162, Department of DefenceGoogle Scholar
  16. MacLennan BJ (1983) Principles of programming languages: design, evaluation and implementation. CBS College Publishing, New York, NYMATHGoogle Scholar
  17. Miller GA (1956) The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol Rev 63:81–97CrossRefGoogle Scholar
  18. Omodei MM, Wearing AJ, McLennan J, Elliott GC, Clancy JM (2004) More is better? Problems of self regulation in naturalistic decision making settings. In: Proceedings of the 5th Naturalistic Decision Making Conference, Stockholm, SwedenGoogle Scholar
  19. Ostrom T (1969) The relationship between the affective, behavioural and cognitive components of attitude. J Exp Soc Psychol 5(1):12CrossRefGoogle Scholar
  20. Reason J (1990) Human error. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  21. Rosenberg MJ, Hovland CI (1960) Cognitive, affective, and behavioral components of attitudes. In: Hovland CI, Rosenberg MJ (eds) Attitude organization and change. Yale University Press, New Haven, CTGoogle Scholar
  22. Saulwick A (2014) Lexpresso: a controlled natural language. In: Proceedings of CNL 2014, 4th International Workshop on Controlled Natural Language, Galway, Ireland, August 20–22, 2014Google Scholar
  23. Shneiderman B (1982) The future of interactive systems and the emergence of direct manipulation. Behav Inf Technol 1(3):237–256CrossRefGoogle Scholar
  24. Stell JG (2000) Boolean connection algebras: a new approach to the region-connection calculus. Artif Intell 122:111–136CrossRefMathSciNetMATHGoogle Scholar
  25. Taplin P, Fox G, Coleman M, Wark S, Lambert DA (2001). Situation awareness using a virtual adviser. In: Talking Head Workshop, OzCHI 2001, Fremantle, WA, AustraliaGoogle Scholar
  26. White FE (1988) A model for data fusion. In: Proceedings of the 1st National Symposium on Sensor Fusion, Vol. 2, Chicago, pp. 143–158Google Scholar
  27. Wierzbicka A (1990) Emotions across languages and cultures. Cambridge University Press, CambridgeGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Defence Science and Technology GroupAdelaideAustralia

Personalised recommendations