In trying to understand how a human operator interacts with a complex system, it is important both from a theoretical and an applied viewpoint that we build a model of the human's behavior in such an environment. This paper briefly reviews different models of the human operator and characterizes them in terms of four conceptual dimensions: purpose, structure, content, and specificity. Methodological issues in operator modeling are also considered.
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References
1.
BaronS.KleinmanD. L.LevisonW. H. (1970). An optimal control model of human response. Automatica, 5, 337–369.
2.
CardS. K.MoranT. P.NewellA. (1983). The psychology of human-computer interaction.Hillsdale, N. J.: Lawrence Erlbaum Associates.
3.
deKleerJ.BrownJ. S. (1983). Assumptions and ambiguities in mechanistic mental models. In GentnerD.StevensA. L. (Eds.), Mental models (pp. 155–190). Hillsdale, N. J.: Lawrence Erlbaum Associates.
4.
FathJ. L.MitchellC. M.GovindarajT. (1986). A methodology for development of a computer aided instruction program in complex, dynamic systems. Proceedings IEEE International Conference on Systems, Man, and Cybernetics (pp. 1216–1221). New York: IEEE.
5.
GoodsteinL. P.RasmussenJ. (in press). Representation of process state, structure, and control. Travail Humaine.
6.
HuntR. M.RouseW. B. (1984). A fuzzy rule-based model of human problem solving. IEEE Transactions on Systems, Man, and Cybernetics, SMC-14, 112–120.
7.
KellyC. R. (1968). Manual and automatic control.New York: Wiley.
8.
KierasD. E.BovairS. (1984). The role of a mental model in learning to operate a device. Cognitive Science, 8, 255–273.
9.
KierasD. E.PolsonP. G. (1983). An approach to the formal analysis of user complexity. International Journal of Man-Machine Studies.
10.
KnaueperA.RouseW. B. (1985). A rule-based model of human problem-solving behavior in dynamic environments. IEEE Transactions on Systems, Man, and Cybernetics, SMC-15, 708–719.
11.
MillerR. A. (1985). A systems approach to modeling discrete control performance. In RouseW. B. (Ed.), Advances in Man-Machine Systems Research, Vol. 2, (pp. 177–248). New York: JAI Press.
12.
MitchellC. M. (1987). GT-MSOCC: A research domain for modeling human-computer interaction and aiding decision making in supervisory control systems. IEEE Transactions on Systems, Man, and Cybernetics, to appear.
13.
MitchellC. M.MillerR. A. (1986). A discrete control model of operator function: A methodology for information display design. IEEE Transactions on Systems, Man, and Cybernetics, SMC-16, 343–357.
14.
MitchellC. M.RubinK. S.GovindarajT. (1986). OFMspert: An operator function model expert system. Proceedings IEEE International Conference on Systems, Man, and Cybernetics (pp. 282–285). New York: IEEE.
15.
MitchellC. M.SaisiD. L. (in press). Use of model-based qualitative icons and adaptive windows in workstations for supervisory control systems. IEEE Transactions on Systems, Man, and Cybernetics, SMC-17.
16.
MiyataY. (1984). The control of multiple activities: A model of kitchen behavior. Institute for Cognitive Science Report C-015, University of California at San Diego, La Jolla, CA.
17.
MorayN. (1976). Attention, control, and sampling behavior. In SheridanT. B.JohannsenG. (Eds.), Monitoring Behavior and Supervisory Control (pp. 221–244). New York: Plenum.
18.
MorayN. (1981). Feedback and the control of skilled behavior. In HoldingD. (Ed.), Human skills (pp. 15–39). New York: Wiley.
19.
NewellA.SimonH. A. (1972). Human problem solving.Englewood Cliffs, N. J.: Prentice Hall.
20.
NiiH. P. (1986). Blackboard systems. AI Magazine, 7–2, 7–3.
21.
RasmussenJ. (1976). Outlines of a hybrid model of the process plant operator. In SheridanT. B.JohannsenG. (Eds.), Monitoring behavior and supervisory control (pp. 371–384). New York: Plenum.
22.
RasmussenJ. (1981). Models of mental strategies in process plant diagnosis. In RasmussenJ.RouseW. B. (Eds.), Human detection and diagnosis of system failures.New York: Plenum.
23.
RasmussenJ. (1983). Skills, rules, knowledge: Signals, signs, and symbols and other distinctions in human performance models. IEEE Transactions on Systems, Man, and Cybernetics, SMC-13, 257–267.
24.
RasmussenJ. (1986). Information processing and human-machine interaction: An approach to cognitive engineering.New York: North-Holland.
25.
RasmussenJ. (1987). Mental models and their implications for design. Sixth Workshop on Informatics and Psychology: Mental Models and Human-Computer Interaction.
26.
RasmussenJ.RouseW. B. (1981). Human detection and diagnosis of system failures.New York: Plenum.
27.
RouseW. B. (1980). Systems engineering models of human-machine interaction.Amsterdam: North Holland.
28.
RouseW. B. (1982). Models of human problem solving: Detection, diagnosis and compensation for system failures. Automatica, 19, 613–625.
29.
RouseW. B.MorrisN. M. (1986). On looking into the black box: Prospects and limits in the search for mental models. Psychological Bulletin, 100, 349–363.
30.
RubinK. S.MitchellC. M.JonesP. M. (1987). OFMspert: An operator function model expert system. To appear in Proceedings Fourth Mexican National Artificial Intelligence Conference.
31.
RubinK. S.JonesP. M.MitchellC. M. (1987). OFMspert: Application of a blackboard architecture to infer operator intentions in real time decision making. Submitted for publication.
32.
SandersonP. M. (1985). Cognitive models and the discovery of structure of complex systems. PhD thesis, University of Toronto, Canada.
33.
SleemanD.BrownJ. S. (Eds.) (1982). Intelligent tutoring systems.Orlando, FL: Academic Press.
34.
VicenteK. J. (1987). The cognitive engineering of visual displays for complex systems. Department of Industrial Engineering and Operations Research, Virginia Polytechnic Institute and State University, Blacksburg, VA.
35.
WickensC. D. (1984). Engineering psychology and human performance.Columbus, OH: Charles Merrill.
36.
WoodsD. D. (1986). Cognitive technologies: The design of joint human- machine cognitive systems. The AI Magazine, 6, pp. 86–92.
37.
WoodsD. D.HollnagelE. (in press). Mapping cognitive demands in complex problem solving worlds. International Journal of Man-Machine Studies, 26.
38.
WoodsD. D.RothE. M. (in press). Cognitive systems engineering. In HelanderM., (Ed.), Handbook of human-computer interaction.
39.
ZinserK.HennemanR. L. (1986). Evaluation of a model of human performance in monitoring and controlling a large scale system. Proceedings IEEE Conference on Systems, Man, and Cybernetics.New York: IEEE
