Models of Procedural Control for Human Performance Simulation

Abstract

This paper describes and evaluates two general techniques to simulate human performance of procedural tasks. A procedural task is characterized as a partial ordering of task elements in which the control of task-element sequencing is represented within the task, rather than as an interaction between the task and the environment in which the task is performed. The primary concern in simulating the performance of procedures is determining the mechanism that controls task-element sequencing. Two modeling frameworks have been used to represent task-element sequencing. The first method represents the constraints on task-element sequencing directly in a network. Am second method represents sequencing constraints indirectly as a set of production rules. Both frameworks offer considerable generality and flexibility in the kinds of structures that can be represented. The relative advantages of the two methods depend upon the questions addressed by the model and the characteristics of the tasks being modeled.

Get full access to this article

View all access options for this article.

References

Aagard, J. A. , and Braby, R. (1976). Learning guidelines and algorithms for types of training objectives (TAEG Report No. 23). Orlando, FL: Training and Evaluation Group.

Anderson, J. R. (1981). Cognitive skills and their acquisition. Hillsdale, NJ: Erlbaum.

Anderson, J. R. (1982). Acquisition of cognitive skill. psychological Review, 89, 369–406.

Chomsky, A. N. (1965). Aspects of the theory of syntax. Cambridge, MA: M.I.T. Press.

Duket, S. D. , Wortman, D. B. , Seifert, D. J. , Hann, R. L. , and Chubb, G. P. (1978). Documentation for the SA/NT simulation program (AMRL-TR-77-63). Dayton, OH: U.S. Air Force Aerospace Medical Research Laboratory.

Ernst, G. W. , and Newell, A. (1969). CPS: A case study in generality and problem solving. New York: Academic Press.

Georgeff, M. P. (1982). Procedural control in production systems. Artificial Intelligence, 18, 175–201.

Lewis, C. H. (1978). Production system models of practice effects. Unpublished doctoral dissertation, University of Michigan, Ann Arbor, MI.

Lewis, C. H. (1981). Skill in algebra. In J. R. Anderson (Ed.), Cognitive skills and their acquisition (pp. 85–110). Hillsdale, NJ: Erlbaum.

10.

Newell, A. (1973). Production systems: Models of control structures. In W. G. Chase (Ed.), Visual information processing (pp. 283–308).New York: Academic Press.

11.

Pew, R. W. , and Baron, S. (1983). Perspectives on human performance modelling. Automatica, 19, 663–676.

12.

Pew, R. W. , Baron, S. , Feehrer, C. E. , and Miller, D. C. (1977). Critical review and analysis of performance models applicable to man-machine systems evaluation (Report No. 3446). Cambridge, MA: Bolt Beranek and Newman, Inc.

13.

Rychener, M. D. , and Newell, A. (1978). An instructable production system: Basic design issues. In D. A. Waterman and F. Hayes-Roth (Eds.), Pattern-directed inference systems (pp. 135–153). New York: Elsevier.

14.

Sacerdoti, E. D. (1977). A structure for plans and behavior. New York: Elsevier.

15.

Siegel, A. I. , and Wolf, J. J. (1969). Man-machine simulation models. New York: Wiley.

16.

Sticha, P. J. , Edwards, T. D. , and Patterson, J. F. (1984). An analytic model of learning and performance of annor procedures (ARI Research Note 84-12). Alexandria, VA: U.S. Army Research Institute for the Behavioral and Social Sciences.

17.

Sticha, P. J. , Knerr, C. M. , and Goldberg, S. L. (1983). Simulating human learning and retention of procedures. In Proceedings of the International Conference on Simulators (pp. 105–109). London: Institution of Electrical Engineers.

18.

Strieb, M. I. , Glenn, F. A. , and Wherry, R. J., Jr. (1978). The human operator simulator: HOS study guide (Technical Report TR-1320, Vol. 9). Willow Grove, PA: Analytics. (AD-A094353)

19.

Strieb, M. I. , and Wherry, R. J., Jr. (1979). An introduction to the human operator simulator (Technical Report TR 1400.02D). Willow Grove, PA: Analytics. (AD-A097520)

20.

Waterman, D. A. , and Hayes-Roth, F. (1978). An overview of pattern-directed inference systems. In D. A. Waterman and F. Hayes-Roth (Eds.), Pattern-directed inference systems (pp. 3–22). New York: Academic Press.

21.

Woods, W. A. (1970). Transition network grammars for natural language analysis. Communications of the ACM, 13, 591–606.

22.

Wortman, O. B. , Duket, S. D. , Seifert, D. J. , Hann, R. L. , and Chubb, G. P. (1978). Simulation using SAINT: A user-oriented instruction manual (AMRL-TR-77-61). Dayton, OH: U.S. Air Force Aerospace Medical Research Laboratory