Yili Liu
Omer Tsimhoni
Skip Abstract Section
Abstract
Queueing Network-Model Human Processor (QN-MHP) is a computational architecture that integrates two complementary approaches to cognitive modeling: the queueing network approach and the symbolic approach (exemplified by the MHP/GOMS family of models, ACT-R, EPIC, and SOAR). Queueing networks are particularly suited for modeling parallel activities and complex structures. Symbolic models have particular strength in generating a person's actions in specific task situations. By integrating the two approaches, QN-MHP offers an architecture for mathematical modeling and real-time generation of concurrent activities in a truly concurrent manner. QN-MHP expands the three discrete serial stages of MHP, of perceptual, cognitive, and motor processing, into three continuous-transmission subnetworks of servers, each performing distinct psychological functions specified with a GOMS-style language. Multitask performance emerges as the behavior of multiple streams of information flowing through a network, with no need to devise complex, task-specific procedures to either interleave production rules into a serial program (ACT-R), or for an executive process to interactively control task processes (EPIC). Using QN-MHP, a driver performance model was created and interfaced with a driving simulator to perform a vehicle steering, and a map reading task concurrently and in real time. The performance data of the model are similar to human subjects performing the same tasks.
- Adams, M., Tenney, Y., and Pew, R. 1991. Strategic Workload and the Cognitive Management of Advanced Multi-task Systems. CSERIAC SOAR Report, 91--6.Google Scholar
- Anderson, J. R. 1993. Rules of the Mind. Lawrence Erlbaum Associates, Hillsdale, NJ.Google Scholar
- Anderson, J. R. and Bower, G. H. 1973. Human Associative Memory. Lawrence Erlbaum Associates, Mahwah, NJ.Google Scholar
- Anderson, J. R., John, B. E., Just, M. A., Carpenter, P. A., Kieras, D. E., and Meyer, D. E. 1995. Production system models of complex cognition. In Proceedings of the 17th Annual Conference of the Cognitive Science Society. Lawrence Erlbaum Associates, Hillsdale, NJ, 9--12.Google Scholar
- Anderson, J. R. and Lebiere, C. Eds. 1998. Atomic Components of Thought. Lawrence Erlbaum Associates, Hillsdale, N.J.Google Scholar
- Anderson, J. R. and Lebiere, C. 2003. The Newell test for a theory of cognition. Behavioral and Brain Sciences 26, 587--601.Google Scholar
- Anderson, J. R., Matessa, M., and Lebiere, C. 1997. ACT-R: A theory of higher level cognition and its relation to visual attention. Hum.-Comput. Inter. 12, 439--462. Google Scholar
- Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., and Qin, Y. 2004. An integrated theory of the mind. Psych. Rev. 111, 1036--1060.Google Scholar
- Baddeley, A. 1992. Working memory. Science 255, 556--559.Google Scholar
- Baddeley, A. 1998. Recent developments in working memory. Current Opinion in Neurobiology 8, 234--238.Google Scholar
- Baron, S., Kruser, D., and Huey, B. Eds. 1990. Quantitative Modeling of Human Performance in Complex, Dynamic Systems. National Academy Press, Washington, DC.Google Scholar
- Baron, S., Zacharias, G., Muralidharan, R., and Lancraft, R. 1980. PROCRU: A Model for Analyzing Flight Crew Procedures in Approach to Landing. NASA-CR-1523397.Google Scholar
- Biederman, I. 1987. Recognition-by-components: A theory of human image understanding. Psychol. Rev. 94, 2, 115--147.Google Scholar
- Boxma, O. and Daduna, H. 1990. Sojourn times in queueing networks. In Stochastic Analysis of Computer and Communications Systems, H. Takagi Ed. North Holland, Amsterdam, 401--450.Google Scholar
- Byrne, M. 2001. ACT-R/PM and menu selection: Applying a cognitive architecture to HCI. Int. J. Hum-Comput. Studies, 55 41--84.Google Scholar
- Byrne, M. and Anderson, J. R. 1998. Perception and action. In The Atomic Components of Thought, J. R. Anderson and C. Lebiere, Eds. Lawrence Erlbaum Associates, Hillsdale, NJ.Google Scholar
- Byrne, M. and Anderson, J. R. 2001. Serial modules in parallel: The psychological refractory period and perfect time-sharing. Psych. Rev. 108, 847--868.Google Scholar
- Buzen, J. 1976. Fundamental operational laws of computer system performance. Acta Informatica 7, 167--182.Google Scholar
- Carbonell, J. 1966. A queueing model of many-instrument visual sampling. IEEE Trans. HFE-4, 157--164.Google Scholar
- Card, S., Moran, T. P., and Newell, A. 1983. The Psychology of Human-Computer Interaction. Lawrence Erlbaum Associates, Hillsdale, NJ. Google Scholar
- Card, S., and Newell, A. 1990. Cognitive architectures. In Quantitative Modeling of Human Performance in Complex, Dynamic Systems. S. Baron, D. Kruser and B. Huey, Eds. National Academy Press, Washington, DC.Google Scholar
- Carter, R. 1998. Mapping the Mind. The University of California Press, Berkeley, CA.Google Scholar
- Chu, Y. and Rouse, W. 1979. Adaptive allocation of decision making responsibility between human and computer in multi-task situations. IEEE Trans. SMC-9, 769--778.Google Scholar
- Courtney, S. and Ungerleider, L. 1997. What fMRI has taught us about human vision. Current Opinion in Neurobiology 7, 554--561.Google Scholar
- Denning, P. and Buzen, J. 1978. The operational analysis of queueing network models. Comput. Surv. 10, 225--261. Google Scholar
- Diaper, D. 1989. Task Analysis for Human Computer Interaction. Prentice Hall. Google Scholar
- Disney, R. and Konig, D. 1985. Queueing networks: A survey of their random processes. SIAM Rev. 27, 335--403.Google Scholar
- Donders, F. C. 1868/1969. Over de snelheid van psychische processen {On the speed of mental processes}. In Attention and Performance 2, W. G. Koster Ed. North-Holland, Amsterdam, 412--431 (Original work published in 1868).Google Scholar
- Donges, E. 1978. A two-level model of driver steering behavior. Human Factors 20, 691--707.Google Scholar
- Duncan, J., Emslie, H., Williams, P., Johnson, R., and Freer, C. 1996. Intelligence and the frontal lobe: The organization of goal-directed behavior. Coqnat. Psych. 30, 251--303.Google Scholar
- Elkind, J. I., Card, S. K., Hochberg, J., and Huey, B. M. Eds. 1990. Human Performance Models for Computer-aided Engineering, Academic Press, Inc., San Diego.Google Scholar
- Feyen, R. 2002. Modeling Human Performance using the Queueing Network---Model Human Processor (QN-MHP). Doctoral Dissertation. Department of Industrial and Operations Engineering, University of Michigan. Google Scholar
- Feyen, R. and Liu, Y. 2001a. Modeling Task Performance Using the Queuing Network-Model Human Processor (QN-MHP). In Proceedings of the Fourth International Conference on Cognitive Modeling. E. M. Altmann, A. Cleermans, C. D. Schunn, and W. D. Gray Eds. Lawrence Erlbaum Associates, Mahwah, NJ.Google Scholar
- Feyen, R. and Liu, Y. 2001b. The Queuing Network-Model Human Processor (QN-MHP): An engineering approach for modeling cognitive performance. In Proceedings of the 45th Annual Meeting of the Human Factors and Ergonomics Society, San Diego, CA.Google Scholar
- Frackiowiak, R. S., Friston, K. J., Frith, C. D., and Mazziotta, J. C. Eds. 1997. Human Brain Function. Academic Press, London, UK.Google Scholar
- George-Maletta, K., Hunter, D. R., Brook, A., Lenner J., and Green, P. 1998. Preliminary examinations of the time to read electronic maps: The effects of text and graphic characteristics. Tech. rep. UMTRI-98-36, The University of Michigan Transportation Research Institute Ann Arbor, MI.Google Scholar
- Gilman, S. and Newman, S. 1992. Manter and Gatz's Essentials of Clinical Neuroanatomy and Neurophysiology (8th edition). F. A. Davis, Philadelphia, PA.Google Scholar
- Godthepet, J., Milgram, P., and Blaauw, G. J. 1984. The development of a time-realted measure to describe driving strategy. Human Factors 26, 3, 257--368.Google Scholar
- Gray, W., John, B., and Atwood, M. 1993. Project Ernestine: Validating a GOMS analysis for predicting and explaining real-world performance. Hum. Comput. Inter. 8, 3, 237--309.Google Scholar
- Greenstein, J. and Rouse, W. 1982. A model of human decision making in multiple process monitoring situations. IEEE Trans. SMC-12, 182--193.Google Scholar
- Harrell, C. R., Bateman, R. E., Gogg, T. J., and Mott, J. R. A. 1995. System Improvement Using Simulation 3rd Ed. PROMODEL Corporation, Orem, Utah.Google Scholar
- Hildreth, E. C., Beusmans, J. M. H., Boer, E. R., and Royden, C. S. 2000. From vision to action: Experiments and models of steering control during driving. J. Exper. Psych.: Human Perception and Performance 26, 3, 1106--1132.Google Scholar
- Hornof, A. J. 1999. Computational models of the perceptual, cognitive, and motor processes involved in the visual search of pull-down menus and computer screens. Doctoral dissertation. University of Michigan. Google Scholar
- John, B. E. 1996. TYPIST: A theory of performance in skilled typing. Hum. Comput. Inter. 11, 321--355. Google Scholar
- John, B. E. and Gray, W. 1995. GOMS analysis of parallel activities. Tutorial notes, CHI. Denver Colorado, May 7--11, 1995.Google Scholar
- John, B. E. and Kieras, D. E. 1996a. Using GOMS for user interface design and evaluation: Which technique? ACM Trans. Hum.-Comput. Inter. 3, 4, 287--319. Google Scholar
- John, B. E. and Kieras, D. E. 1996b. The GOMS family of user interface analysis techniques: Comparison and contrast. ACM Trans. Hum.-Comput. Inter. 3, 4, 320--351. Google Scholar
- John, B. E., Prevas, K., Salvucci, D., and Koedinger, K. 2004. Predictive human performance modeling made easy. In Proceedings of CHI 2004. Vienna, Austria, April 2004. Google Scholar
- Just, M. A. and Carpenter, P. N. 1992. A capacity theory of comprehension: individual differences in working memory. Psych. Rev. 99, 122--149.Google Scholar
- Kieras, D. 1999. A guide to GOMS usability evaluation using GOMSL and GLEAN3. University of Michigan Department of Electrical Engineering and Computer Science On-line publication.Google Scholar
- Kieras, D. E. 1988. Towards a practical GOMS model methodology for user interface design. In The handbook of human-computer interaction. M. Helander Ed. North-Holland Elsevier, Amsterdam.Google Scholar
- Kieras, D. E. and Meyer, D. E. 1997. An overview of the EPIC architecture for cognition and performance with application to human-computer interaction. Hum.-Comput. Inter. 12, 4, 391--438. Google Scholar
- Kieras, D. E., Wood, S. D., and Meyer, D. E. 1997. Predictive engineering models based on the EPIC architecture for a multimodal high-performance human-computer interaction task. ACM Trans. Comput.-Hum. Inter. 4, 230--275. Google Scholar
- Kirwan, B. and Ainsworth, L. K. Eds. 1992. A Guide To Task Analysis. Taylor and Francis.Google Scholar
- Kleinman, D. L. and Curry, R. E. 1977. Some new control theoretic models for human operator display monitoring. IEEE Trans. SMC-7, 778--784.Google Scholar
- Laird, J. E., Newell, A., and Rosenbloom, P. S. 1987. Soar: An architecture for general intelligence. Artificial Intelligence 33, 1--64. Google Scholar
- Land, M. F. and Lee, D. N. 1994. Where we look when we steer. Nature 369, 742--744.Google Scholar
- Laughery, K. 1989. Micro SAINT: A tool for modeling human performance in systems. In Applications of Human Performance Models to System Design, G. McMillan et al., Eds. Plenum, New York, 219--230.Google Scholar
- Laughery, K. and Corker, K. 1997. Computer modeling and simulation. In Handbook of Human Factors and Ergonomics (2nd edition), G. Salvendy Ed. Wiley, New York.Google Scholar
- Leibowitz, H. W. and Owens, D. A. 1977. Nighttime driving accidents and selective visual degradation. Science 197, 422--423.Google Scholar
- Levison, W. H., Simsek, O., Bittner, A. C., and Hunn, S. J. 2001. Computational techniques used in the driver performance model of the interactive highway safety design model. Transportion Research Record 1779, 17--25.Google Scholar
- Lim, J. and Liu, Y. 2004a. A queueing network model of menu selection and visual search. In Proceedings of the 47 Annual Conference of the Human Factors and Ergonomics Society, 1846--1850.Google Scholar
- Lim, J. and Liu, Y. 2004b. A queueing network model for eye movement. In Proceedings of the 2004 International Conference on Cognitive Modeling, Pittsburg, PA, 154--159.Google Scholar
- Liu, Y. 1994. Queuing networks as models of human performance and human-computer systems. In Proceedings of the '94 Symposium on Human Interaction with Complex Systems, 256--270.Google Scholar
- Liu, Y. 1996. Queuing network modeling of elementary mental processes. Psych. Rev, 103, 116--136.Google Scholar
- Liu, Y. 1997. Queuing network modeling of human performance of concurrent spatial or verbal tasks. IEEE Trans. Syst., Man, and Cybernetics 27, 195--207. Google Scholar
- Martin, J. H. 1989. Neuroanatomy: Text and Atlas. Elsevier, New York, NY.Google Scholar
- McClelland, J. 1979. On the time relations of mental processes: An examination of systems of processes in cascade. Psych. Rev. 86, 287--330.Google Scholar
- McClelland, J. L. and Rumelhart, D. E. 1986. Parallel Distributed Processing: Explorations in the Microstructure of Cognition (vol. 2). MIT Press, Cambridge, MA. Google Scholar
- McRuer, D. T., Allen, R. W., Weir, D. H., and Klein, R. H. 1977. New results in driver steering control models. Human Factors 19, 4, 381--397.Google Scholar
- Meyer, D. E., and Kieras, D. E. 1997a. A computational theory of executive cognitive processes and multiple-task performance: Part 1. Basic mechanisms. Psych. Rev. 104, 3--65.Google Scholar
- Meyer, D. E., and Kieras, D. E. 1997b. A computational theory of executive cognitive processes and multiple-task performance: Part 2. Accounts of psychological refractory period phenomena. Psych. Rev. 104, 749--791.Google Scholar
- Meyer, D. E. and Kieras, D. E. 1999. Précis to a practical unified theory of cognition and action: Some lessons from EPIC computational models of human multiple-task performance. In Attention and Performance XVII. Cognitive Regulation of Performance: Interaction of Theory and Application. D. Gopher and A. Koriat Eds., MIT Press, Cambridge, MA. 17--88.Google Scholar
- Miller, J. O. 1993. A queue-series model for reaction time, with discrete-stage and continuous-flow models as special cases. Psych. Rev. 100, 702--715.Google Scholar
- Mourant, R. R. and Rockwell, T. H. 1970. Mapping eye-movement patterns to the visual scene in driving: An exploratory study. Human Factors 12, 81--87.Google Scholar
- Newell, A. 1973. You can't play 20 questions with nature and win: Projective comments on the papers of this symposium. In Visual Information Processing. W. G. Chase Ed. Plenum Press, New York.Google Scholar
- Newell, A. 1990. Unified theories of cognition. Harvard University Press, Cambridge, MA. Google Scholar
- Niebel, B. 1993. Motion and Time Study (9th ed.). Irwin, Boston, MA.Google Scholar
- Nilsen, E. L. 1991. Perceptual-motor control in human-computer integration. Doctoral dissertation. Department of Psychology, University of Michigan. Google Scholar
- North, R. and Riley, V. 1989. W/INDEX: A predictive model of operator workload. In Applications of Human Performance Models to System Design, G. McMillan et al., Eds., 81--89, Plenum, New York.Google Scholar
- Olson, J. R. and Olson, G. M. 1990. The growth of cognitive modeling in human-computer interaction since GOMS. Hum.-Comput. Inter. 5, 221--265.Google Scholar
- Owens, D. A. and Tyrrell, R. A. 1999. Effects of luminance, blur, and age on nighttime visual guidance: A test of the selective degradation hypothesis. J. Exper. Psych. Applied 5, 115--128.Google Scholar
- Passingham, R. E. 1987. Cues for movement in monkeys (Macaca mulatta) with lesions in premotor cortex. Behav. Neorosci. 100, 3, 695--703.Google Scholar
- Pattipati, K. R., Kleinman, D. L., and Ephrath, A. R. 1983. A dynamic decision model of human task selection performance. IEEE Trans. SMC-13, 145--166.Google Scholar
- Pew, R. W. and Baron, S. 1983. Perspectives on human performance modeling. Automatica 19, 6, 663--676.Google Scholar
- Pritchard, T. C. and Alloway, K. D. 1999. Medical Neuroscience. Fence Creek Publishing, Madison, CT.Google Scholar
- Quinn, G. and McConnell, J. 1996. Irrelevant pictures in visual working memory. Quart. J. Exper. Psych. 49, 2, 200--215.Google Scholar
- Remington, R. W., Less, S., Ravinder, U., and Freed, M. 2004. Modeling patterns of performance in air traffic control operations. In Proceedings of International Conference on Computational and Experimental Engineering and Sciences (ICCES '04). Madeira, Portugal. July, 2004.Google Scholar
- Reymond, G., Kemeny, A., Droulez, J., and Berthoz, A. 2001. Role of lateral acceleration in driving: experiments on a real vehicle and a driving simulator. Human Factors 43, 3, 483--495.Google Scholar
- Roberts, A. C., Robbins, T. W., and Wieskrantz, L. Eds. 1996. Executive and cognitive functions of the prefrontal cortex. Philosoph. Trans. Royal Society of London (Biology) 351, 1387--1527.Google Scholar
- Roland, P. 1993. Brain Activation. Wiley, New York.Google Scholar
- Rosenbaum, D. A. 1991. Human Motor Control. Academic Press, New York.Google Scholar
- Rouse, W. B. 1980. Systems Engineering Models of Human-Machine Interaction, Elsevier North-Holland, New York.Google Scholar
- Salthouse, T. A. 1986. Perceptual, cognitive, and motoric aspects of transcription typing. Psych. Bull. 99, 3, 303--31.Google Scholar
- Salvucci, D. D. 2001. Predicting the effects of in-car interface use on driver performance: An integrated model approach. Inter. J. Hum.-Comput. Studies 55, 85--107.Google Scholar
- Salvucci, D. D., Boer, E. R., and Liu, A. 2001. Toward an integrated model of driver behavior in a cognitive architecture. Transportation Research Record, 17--79.Google Scholar
- Salvucci, D. D. and Macuga, K. L. 2002. Predicting the effects of cell-phone dialing on driver performance. In Proceedings of the Fourth International Conference on Cognitive Modeling. E. M. Altmann, A. Cleermans, C. D. Schunn, and W. D. Gray, Eds. Lawrence Erlbaum Associates, Mahwah, NJ.Google Scholar
- Salvucci, D. D. and Gray, R. 2004. A two-point visual control model of steering. Perception, 33, 1233--1248.Google Scholar
- Schmidt, D. 1978. A queueing analysis of the air traffic controller's workload. IEEE Trans. SMC-8, 492--493.Google Scholar
- Schweickert, R. 1978. A critical path generalization of the additive factor method: Analysis of a Stroop task. J. Mathem. Psych. 18, 105--139.Google Scholar
- Senders, J. W. 1964. The human operator as a monitor and controller of multidegree freedom systems. IEEE Trans. HFE, HFE-5, 2--5.Google Scholar
- Senders, J. W. and Posner, M. 1976. A queueing model of monitoring and supervisory behavior. In Monitoring Behavior and Supervisory Control, T. Sheridan and G. Johannsen, Eds., Plenum, New York.Google Scholar
- Sheridan, T. 1972. On how often the supervisor should sample. IEEE Trans. SSS-6, 140--145.Google Scholar
- Siegal, A. I. and Wolf, J. J. 1969. Man-machine Simulation Models, Wiley, New York.Google Scholar
- Smith, E., Jonides, J., and Koeppe, R. A. 1996. Dissociating verbal and spatial working memory using PET. Cerbral Cortey 6, 11--20.Google Scholar
- Sternberg, S. 1969. The discovery of processing stages: Extensions of Donders's method. Acta Psychologica 30, 276--235.Google Scholar
- Summala, H. 1998. Forced peripheral vision driving paradigm: Evidence for the hypothesis that car drivers learn to keep in lane with peripheral vision. In Vision in Vehicles VI, A. G. Gale, Ed. Elsevier Science Publishers, Amsterdam, 51--60.Google Scholar
- Tsimhoni, O. 2004. Visual sampling of in-vehicle displays while driving: Empirical findings and a queueing network cognitive model. Doctoral Dissertation. Department of Industrial and Operations Engineering. University of Michigan.Google Scholar
- Tsimhoni, O. and Green, P. 2001. Visual demand of driving and the execution of display-intensive, in-vehicle tasks. In Proceedings of the Human Factors and Ergonomics Society 45th Annual Meeting. Santa Monica, CA. Human Factors and Ergonomics Society.Google Scholar
- Tsimhoni, O. and Liu, Y. 2003a. Modeling steering using the queueing network model human processor (QN-MHP). In Proceedings of the Human Factors and Ergonomics Society 47th Annual Meeting.Google Scholar
- Tsimhoni, O. and Liu, Y. 2003b. Steering a driving simulator using the queueing network-model human processor (QN-MHP). In Driving Assessment 2003: International Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design. D. V. McGehee, J. D. Lee, and M. Rizzo, Eds.Google Scholar
- Tulga, M. K. and Sheridan, T. 1980. Dynamic decisions and workload in multitask supervisory control. IEEE Trans. SMC-10, 217--232.Google Scholar
- van Selst, M., Ruthruff, E., and Johnston, J. C. 1999. Can practice eliminate the psychological refractory period effect? J. Exper. Psych.: Human Perception and Performance 25, 5, 1268--1283.Google Scholar
- van Winsum, W., Brookhuis, K. A., and de Waard, D. 2000. A compansion of different ways to approximate time-to-line crossing (TLC) during car driving. Accident, Analysis and Prevention 32, 1, 47--56.Google Scholar
- Walden, R. and Rouse, W. 1978. A queueing model of pilot decision making in a multitask flight management situation. IEEE Trans. SMC-8, 867--875.Google Scholar
- Wallis, G., Chatziastros, A., and Bulthoff, H. 2002. An unexpected role for visual feedback in vehicle steering control. Current Biology 12, 295--299.Google Scholar
- Wherry, R. J. 1976. The human operator simulator---HOS. In Monitoring Behavior and Supervisory Control. T. B. Sheridan and G. Johannsen, Eds. Plenum Press, New York.Google Scholar
- Wickens, C. D. 1984. Processing resources in attention. In Varieties of Attention, R. Parasuraman and D. Davis, Eds. Academic Press, New York.Google Scholar
- Wickens, C. D. and Liu, Y. 1988. Codes and modalities in multiple resources: A success and a qualification. Human Factors 30, 599-616. Google Scholar
- Wu, C. and Liu, Y. 2004a. Modeling psychological refractory period (PRP) and practice effect on PRP with queuing networks and reinforcement learning algorithms. In Proceedings of 2004 International Conference on Cognitive Modeling, Pittsburg, PA, 320--325.Google Scholar
- Wu, C. and Liu, Y. 2004b. Modeling behavioral and brain imaging phenomena in transcription typing with queuing networks and reinforcement learning algorithms. In Proceedings of 2004 International Conference on Cognitive Modeling, Pittsburg, PA, 314--319.Google Scholar
- Wu, C. and Liu, Y. 2004c. Queueing network modeling of transcription typing. In Proceedings of the 47th Annual Conference of the Human Factors and Ergonomics Society, 381--385.Google Scholar
Index Terms
- Queueing Network-Model Human Processor (QN-MHP): A computational architecture for multitask performance in human-machine systems
Recommendations
Development of an Adaptive Workload Management System Using the Queueing Network-Model Human Processor (QN-MHP)
The risk of vehicle collisions significantly increases when drivers are overloaded with information from in-vehicle systems. One of the solutions to this problem is developing adaptive workload management systems (AWMSs) to dynamically control the rate ...
The evolution of human systems: a brief overview
FAC'11: Proceedings of the 6th international conference on Foundations of augmented cognition: directing the future of adaptive systemsRecently, there has been a profound resurgence interest in expanding the effectiveness of human machine systems. The motivation for this interest stems not only from the growing realization that better designed systems - tailored to augment their user's ...
Comments