Background, structure, and preview of the model comparison

Modeling Human Behavior with Integrated Cognitive Architectures: Comparison, Evaluation, and Validation

Volumn , Issue , 2005, Pages 3-12

  Gluck, Kevin A ^a   Pew, Richard W ^b   Young, Michael J ^a  

^a AIR FORCE RESEARCH LABORATORY   (United States)

^b BBN TECHNOLOGIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84891949723     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4324/9781410613257     Document Type: Chapter

References (18)

1. Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.
2. Anderson, J. R. (1993). Rules of the mind. Mahwah, NJ: Lawrence Erlbaum Associates.
3. Deutsch, S. E., & Benyo, B. (2001). The D-OMAR simulation environment for the AMBR experiments. In the Proceedings of the 10th Annual Conference on Computer-Generated Forces and Behavior Representation (pp. 7-14). Orlando, FL: Division of Continuing Education, University of Central Florida.
4. Deutsch, S. E., MacMillan, J., & Cramer, N. L. (1993). Operator Model Architecture (OMAR) demonstration final report (AL/HR-TR-1996-0161). Wright-Patterson AFB, OH: Armstrong Laboratory, Logistics Research Division.
5. Gigley, H. M., & Chipman, S. F. (1999). Productive interdisciplinarity: The challenge that human learning poses to machine learning. In Proceedings of the 21st Conference of the Cognitive Science Society (p. 2). Mahwah, NJ: Lawrence Erlbaum Associates.
6. Hollnagel, E. (1993). Human reliability analysis: Context and control. London: Academic Press.
7. Just, M. A., Carpenter, P. A., & Varma, S. (1999). Computational modeling of high-level cognition and brain function. Human Brain Mapping, 8, 128-136.
8. Kanerva, P. (1993). Sparse distributed memory and related models. In M. H. Hassoun (Ed.), Associative neural memories: Theory and implementation (pp. 50-76). New York: Oxford University Press.
9. Kintsch, W., Healy, A. F., Hegarty, M., Pennington, B. F., & Salthouse, T. (1999). Models of working memory: Eight questions and some general issues. In A. Miyake & P. Shah (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 412-441). New York: Cambridge University Press.
10. Miyake, A., & Shah, P. (Eds.). (1999). Models of working memory: Mechanisms of active maintenance and executive control. New York: Cambridge University Press.
11. Morrison, J. E. (2004). A review of computer-based human behavior representations and their relation to military simulations (IDA Paper P-3845). Alexandria, VA: Institute for Defense Analyses.
12. Newell, A. (1990). Unified theories of cognition. Cambridge, MA: Harvard University Press.
13. Nosofsky, R. M., Gluck, M., Palmeri, T. J., McKinley, S. C., & Glauthier, P. (1994). Comparing models of rule-based classification learning: A replication and extension of Shepard, Hovland, and Jenkins (1961). Memory & Cognition, 22, 352-369.
14. Pew, R. W., & Mavor, A. S. (Eds.). (1998). Modeling human and organizational behavior: Applications to military simulations. Washington, DC: National Academy Press.
15. Pylyshyn, Z. W. (1991). The role of cognitive architecture in theories of cognition. In K. VanLehn (Ed.), Architectures for intelligence (pp. 189-223). Hillsdale, NJ: Lawrence Erlbaum Associates.
16. Ritter, F. E., Shadbolt, N. R., Elliman, D., Young, R. M., Gobet, F., & Baxter, G. D. (2003). Techniques for modeling human performance in synthetic environments: A supplementary review (HSIACSOAR-2003-01). Wright-Patterson Air Force Base, OH: Human Systems Information Analysis Center.
17. Shepard, R. N., Hovland, C. L., & Jenkins, H. M. (1961). Learning and memorization of classifications, Psychological Monographs, 75(13,Whole No. 517).
18. Young, R. M., Barnard, P., Simon, T., & Whittington, J. (1989). How would your favourite user model cope with these scenarios? SIG CHI Bulletin, 20(4), 51-55.