Principles for Intelligent Decision Aiding

  • Susan G. Hutchins
Part of the The Kluwer International Series in Engineering and Computer Science book series (SECS, volume 372)


The Tactical Decision Making Under Stress (TADMUS) program is being conducted to apply recent developments in decision theory and human-system interaction technology to the design of a decision support system for enhancing tactical decision making under the highly complex conditions involved in antiair warfare scenarios. Our goal is to present decision support information in a format that minimizes any mismatches between the cognitive characteristics of the human decision maker and the design and response characteristics of the decision support system. This includes two major thrusts. The first thrust involves the central hypothesis of the TADMUS program: presenting decision makers with decision support tools which parallel the cognitive strategies they already employ, thus reducing the number of decision-making errors. Hence, prototype display development has been based on decision-making models postulated by naturalistic decision-making theory, such as the recognition-primed decision model and explanation-based reasoning. The second thrust involves incorporating human-system interaction principles which are expected to reduce cognitive processing demands and thereby mitigate decision errors caused by cognitive overload, which have been documented through research and experimentation. Topics include a discussion of: (1) the theoretical background for the TADMUS program; (2) the decision support and human-system interaction principles incorpor-ated to reduce the cognitive processing load on the decision maker (3) a brief description of the types of errors made by decision makers and interpretations of the cause of these errors based on the cognitive psychology literature; and (4) a description of the decision support system.


Decision Maker Decision Support System Situation Awareness Situation Assessment Threat Assessment 
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.


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  1. [1]
    Adams, M. J., Tenney, Y. J., & Pew, R. W. (1995). Situation Awareness and the Cognitive Management of Complex Systems. Human Factors, 37(1), 85–104.CrossRefGoogle Scholar
  2. [2]
    American Psychological Association, Science Agenda, Fall, 1988.Google Scholar
  3. [3]
    Barnett, B. J., Perrin, B. M., & Walrath, L. D. (1993). Bias in Human Decision Making for Tactical Decision Making Under Stress, (Task 1) St. Louis, MO: McDonnell Douglas Corporation.Google Scholar
  4. [4]
    Bower, G. H. (1970). Organizational Factors in Memory. Cognitive Psychology, 1, 18–46.CrossRefGoogle Scholar
  5. [5]
    Broadbent, D. E. (1957). A mechanical model for human attention and immediate memory. Psychological Review, 64, 205–215.CrossRefGoogle Scholar
  6. [6]
    Buck, L. (1989). Human error at sea. Human Factors Bulletin, September, 32 (9), 12.Google Scholar
  7. [7]
    Casey, S. (1993). Set Phasers on Stun and Other True Tales of Design, Technology, and Human Error. Aegean Publishing Company, Santa Barbara, CA.Google Scholar
  8. [8]
    Casner, S. (1991). Task-Analytic Design of Graphic Presenta-tions. Technical Report AIP-145. Departments of Computer Science and Psychology, Carnegie Mellon University and Learning Research and Development Center, University of Pittsburgh, PA.Google Scholar
  9. [9]
    Cohen, M. S. (1993). The Bottom Line: Naturalistic Decision Aiding. In G. Klein, J. Orasanu, R. Calderwood, & C. E. Zsambok (Eds.) Decision Making in Action: Models and Methods (pp. 138–147). Ablex Publishing Corporation, New Jersey.Google Scholar
  10. [10]
    Dawes, R. M. (1971). A case study of graduate admissions: Application of three principles of human decision making. American Psychologist. 34, 571–582.CrossRefGoogle Scholar
  11. [11]
    Dotterway, K. A. (1992). Systematic Analysis of Complex Dynamic Systems: The case of the USS Vincennes. Unpublished master’s thesis, Naval Postgraduate School, Monterey, CA.Google Scholar
  12. [12]
    Endsley, M. R. (1988). Design and evaluation for situational awareness enhancement. Proceedings of the Human Factors 32nd Annual Meeting, 97–101.Google Scholar
  13. [13]
    Federico, P. A. (1995). Expert and novice recognition of similar situations. Human Factors, 37(1), 105–122.CrossRefGoogle Scholar
  14. [14]
    Gruner, W. P. No Time For Decision Making. (1990, November). U.S. Naval Institute Proceedings, 39–41.Google Scholar
  15. [15]
    Harwood, K., Barnett, B., and Wickens, C. (1988). Situational awareness: A conceptual and methodological framework. Proceedings of the Symposium Psychology in the Department of Defense.Google Scholar
  16. [16]
    Hockey, G. R. (1986). Changes in Operator Efficiency as a Function of Environmental Stress, Fatigue, and Circadian Rhythms. In: K. R. Boff, L. Kaufman, J. P. Thomas (Eds.): Handbook of Perception and Human Performance. Wiley, New York.Google Scholar
  17. [17]
    Hutchins, S. G. (in press). Decision-Making Evaluation Facility for Tactical Teams. Naval Command, Control, and Ocean Surveillance Center, RDT&E Division Technical Report, in press, San Diego, CA.Google Scholar
  18. [18]
    Hutchins, S. G. and Kowalski, J. T. (1993). Tactical Decision Making Under Stress: Preliminary Results and Lessons Learned. Proceedings of the 10th Annual Conference on Command and Control Decision Aids. June 1993, Washington, D. C.Google Scholar
  19. [19]
    Hutchins, S. G. and Rummel, B. K. (1995). A Decision Support System for Tactical Decision Making Under Stress. Proceedings of the First International Conference on Command and Control Research and Technology. June 1995, Washington, D. C.Google Scholar
  20. [20]
    Hutchins, S. G. and Westra, D. P. (1995). Patterns of Errors Shown by Experienced Navy Combat Information Center Teams. Proceedings of the 39 th Annual Meeting of the Human Factors and Ergonomics Society, San Diego, CA. October 1995.Google Scholar
  21. [21]
    Hutchins, S. G. and Westra, D. P. (in preparation). TADMUS Baseline Experimental Results. Naval Command, Control, and Ocean Surveillance Center, RDT&E Division Technical Report, in preparation, San Diego, CA.Google Scholar
  22. [22]
    Kaempf, G. L. and Militelo, L. G., (1992). Decision Making in Emergencies, First Offshore Installation Management Conference: Emergency Command Responsibilities Collected Papers, Aberdeen, Scotland.Google Scholar
  23. [23]
    Kaempf, G. L., Wolf, S. and Miller, T. E. (1993). Decision Making in the Aegis Combat Inform.ation Center. In Proceedings of the Human Factors and Ergonomics Society 37th Annual Meeting (pp. 1107–1111). Santa Monica, CA: Human Factors and Ergonomics Society.Google Scholar
  24. [24]
    Kahneman, D., Slovic, P. & Tversky, A. (Eds.) (1982). Judgment under uncertainty: Heuristics and biases. Cambridge: Cambridge University Press.Google Scholar
  25. [25]
    Kirshenbaum, S. S. (1992). Influence of Experience on Informa-tion-Gathering Strategies. Journal of Applied Psychology, 77, 343–352.CrossRefGoogle Scholar
  26. [26]
    Klein, G. A. (1989). Recognition-Primed Decisions. In W. R. Rouse (Ed.) Advances in Man-Machine Systems Research (pp. 47–92), Vol. 5. JAI Press, Inc.Google Scholar
  27. [27]
    Klein, G. A. (1993). A Recognition-Primed Decision (RPD) Model of Rapid Decision Making. In G. A. Klein, J. Orasanu, R. Calderwood, & C. E. Zsambok (Eds.) Decision Making in Action: Models and Methods (pp. 138–147). Ablex Publishing Corporation, New Jersey.Google Scholar
  28. [28]
    Larkin, J. H. and Simon, H. A. (1987). Why a diagram is (sometimes) worth 10,000 words. Cognitive Science, 11, 65–99.CrossRefGoogle Scholar
  29. [29]
    Mosier, (in press). Myths associated with Automated Decision Aids. In G. A. Klein, & C. E. Zsambok (Eds.) Advances in Naturalistic Decision Making: Research and Applications, Hillsdale, NJ: Erlbaum.Google Scholar
  30. [30]
    Mundy, C. E., Jr. (1994). Thunder and Lightning: Joint Littoral Warfare, Joint Force Quarterly, 4, Spring, 45–50.Google Scholar
  31. [31]
    Noble, D. (1989). Application of theory of cognition to situation assessment. Vienna, VA: Engineering Research Associates.Google Scholar
  32. [32]
    Noble, D. (1993). A Model to Support Development of Situation Assessment Aids. In G. A. Klein, J. Orasanu, R. Calderwood, & C. E. Zsambok (Eds.) Decision Making in Action: Models and Methods (pp. 287–305). Ablex Publishing Corporation, New Jersey.Google Scholar
  33. [33]
    Norman, D. A. (1988). The Psychology of Everyday Things. Basic Books, Inc. New York.Google Scholar
  34. [34]
    Norman, D. A. and Bobrow, D. G. (1975). On the data-limited and resourceslimited processes. Cognitive Psychology, 7, 44–64.CrossRefGoogle Scholar
  35. [35]
    Office of Naval Technology. (1992). FY 1993 Program Plan for Tactical Decision-Making Under Stress, Arlington, VA: July 1992.Google Scholar
  36. [36]
    Orasano, J. and Connolly, T. (1993). The Reinvention of Decision Making. In G. A. Klein, J. Orasanu, R. Calderwood and C. E. Zsambok (Eds.), Decision Making in Action: Models and methods. Norwood, NJ: Ablex Publishing Corporation.Google Scholar
  37. [37]
    Paradies, M. (1991). Root Cause Analysis and Human Factors. Human Factors Society Bulletin, 34(8), 1–4.Google Scholar
  38. [38]
    Paradies, M. & Unger, L. (1991). TapRoot Incident Investiga-tion System Manual. Volumes 1–7. System Improvements, Inc. Knoxville, TN.Google Scholar
  39. [39]
    Pennington, N. & Hastie, R (1992). Explaining the Evidence: Tests of the Story Model of Decision Making. Journal of Personality and Social Psychology, Vol. 62, No.2, 189–206.CrossRefGoogle Scholar
  40. [40]
    Pennington, N. & Hastie, R (1993). A theory of Explanation-Based Decision Making. In G. A. Klein, J. Orasanu, R. Calderwood, & C. E. Zsambok (Eds.) Decision Making in Action: Models and Methods (pp. 188–201). Ablex Publishing Corporation, New Jersey.Google Scholar
  41. [41]
    Perrow, C. (1984). Normal Accidents: Living with High Risk Technologies. New York, Basic Books, Inc.Google Scholar
  42. [42]
    Rasmussen, J. (1986). Information Processing and Human-Machine Interaction. In A. P. Sage (Ed.) Series Volume 12, North-Holland, Amsterdam.Google Scholar
  43. [43]
    Roberts, N. C. & Dotterway, K. A. (1995). The Vincennes Incident: Another Player on the Stage? Defense Analysis Vol 11, No.1, pp. 31–45.Google Scholar
  44. [44]
    Salthouse, T. A. (1992). Cognition and Context. Science, 257, 982–983.CrossRefGoogle Scholar
  45. [45]
    Sanderson, P. M. and Fisher, C. (1994). Exploratory Sequential Data Analysis: Foundations. Human Computer Interaction, 9 (3&4), 1994.Google Scholar
  46. [46]
    Sarter, N. B. and Woods, D. D. (1991). Situation awareness: A critical but illdefined phenomenon. The International Journal of Aviation Psychology, 1(1), 45–57.CrossRefGoogle Scholar
  47. [47]
    Schneider, W., and Detweiler, M. (1988). The role of practice in dual-task performance: Toward workload modeling in a connectionist/ control architecture. Human Factors, 30, 539–566.Google Scholar
  48. [48]
    Senders, J. W. & Moray, N. P. (1991). Human Error: Cause, Prediction, and Reduction. Lawrence Erlbaum Associates, New Jersey.Google Scholar
  49. [49]
    Shrestha, L. B., Prince, C., Baker, D. P. and Salas, E., (1995). Understanding Situation Awareness: Concepts, Methods, and Training. Human/Technology Interaction in Complex Systems. Vol 7, W. B. Rouse (Ed.). San Francisco: JAI Press.Google Scholar
  50. [50]
    Simon, H. A. (1978). Information-processing theory of human problem solving. In W. K. Estes (Ed.), Handbook of Learning and Cognitive Processes, Vol 5, Human Information Processing, New York: Wiley.Google Scholar
  51. [51]
    Smith, D. E. and Grossman, J. D. (1993). Understanding and Aiding Decision Making in Time-Constrained and Ambiguous Situations. Unpublished manuscript.Google Scholar
  52. [51]
    Smith, D. E. and Marshall, S. (in press). Applying Hybrid Models of Cognition in Decision Aids. In G. A. Klein, & C. E. Zsambok (Eds.) Advances in Naturalistic Decision Making: Research and Applications, Hillsdale, NJ: Erlbaum.Google Scholar
  53. [53]
    Swets, J. A. (1984). Mathematical models of attention. In R. Parasuraman and R. Davies (Eds.), Varieties of Attention (pp. 183–242). New York: Academic.Google Scholar
  54. [54]
    Tolcott, M. A. & Marvin, F. F. (1988). Reducing the confirmation bias in an evolving situation. Interim Technical Report 88–11, Reston, VA: Decision Science Consortium, Inc.Google Scholar
  55. [55]
    Tolcott, M. A. (1991). Understanding and Aiding Military Decisions. Office of Naval Research European Office. 27th International Applied Psychology Symposium, Stockholm, Sweden, June 1991.Google Scholar
  56. [56]
    Wilson, G. L. & Zarakas, P. (1978). Anatomy of a blackout. IEEE Spectrum, February, 339–346.Google Scholar

Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • Susan G. Hutchins
    • 1
  1. 1.RDT&E DivisionNaval Command, Control and Ocean Surveillance CenterSan DiegoUSA

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