Artificial intelligence (AI) is concerned with the symbol-manipulation processes that produce intelligent action; that is, acts that are arrived at by intelligible reasoning steps that are guided by knowledge of a particular domain. AI areas relevant to human factors and automation include expert systems, natural-language understanding, and intelligent robotics. These topics are reviewed and illustrated. Potential contributions of human factors research to AI are briefly described.
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References
1.
Anderson, J. (1983). The architecture of cogllition. Cambridge, MA: Harvard University Press.
2.
Baker, J. D. (1984). Dipmeter advisor: An expert log analysis system at Schlumberger. In P. H. Winston and K. A. Prendergast (Eds.), The AI business (pp. 51–65). Cambridge, MA: M.I.T. Press.
3.
Blazy, L. (1984a, May 16). Human factors issues in expert systems research. Paper presented at the 1984 Spring Symposium, “The Role of Artificial Intelligence in Human Factors,” Human Factors Society, Potomac Chapter, College Park, MD.
4.
Blazy, L. (1984b).Information processing requirements and needs in using expert systems. Doctoral dissertation, University of Maryland, College Park, MD.
5.
Bogen, R. (1975). MACSYMA reference manual (unnumbered report). Cambridge, MA: M.I.T., Laboratory of Computer Science.
6.
Brachman, R. J., and Smith. B.C. (1980), SIGART70 (special issue on knowledge representation).
7.
Brady, J. M. (1984). Intelligent robots: Connecting perception to action. In P. H. Winston and K. A. Prendergast (Eds.), The AI business (pp. 179–203). Cambridge, MA: M.I.T. Press.
8.
Buchanan, B. G., and Feigenbaum, E. A. (1978). DENDRAL and Meta-DENDRAL: Their applications dimension. Artificial Intelligence, 11, 5–24.
9.
Buchanan, B. G., and Mitchell, T. M. (1977). Model directed learning of production rules. (Report STAN-CS-77–597). Stanford, CA: Stanford University, Computer Science Department. Reprinted in D. A. Waterman and F. Hayes-Roth (Eds.) (1978). Pattern-directed inference systems (pp. 297–312) New York: Academic Press.
10.
Chomsky, N. (1957). Syntactic structures. The Hague: Mouton.
11.
Cullingford, R. E. (1978). Script application.' Computer understanding of newspaper stories. Unpublished doctoral dissertation, Yale University, New Haven, CT.
12.
Davis, R. (1977). Interactive transfer of expertise: Acquisition of new inference rules, International Joint Conference on Artificial Intelligence, 5, 321–328.
13.
DeJong, G. F. (1979). Skimming stories in real time: An experiment in integrated understanding. Unpublished doctoral dissertation, Yale University, New Haven CT.
14.
Duda, R. 0., and Gaschnig, J. G. (1981). Knowledge-based expert systems coming of age. Byte, 6 (9), 238–281.
15.
Duda, R. 0., Gaschnig, J. G., and Hart, O. E. (1979). Model design in the PROSPECTOR consultant system for mineral exploration. In D. Michie (Ed.), Expert systems in the micro-electronic age (pp. 153–167). Edinburgh: Edinburgh University Press.
16.
Fain, J., Gorlin, D., Hayes-Roth, F., Rosenschein, S. J., Sowizral, H., and Waterman, D. (1981). The ROSIE language reference manual (Tech. Report N-1647-ARPA). Santa Monica, CA: Rand Corp.
17.
Feigenbaum, E. A., Buchanan, B. G., and Lederberg, J. (1971). On generality and problem solving: A case study using the DENDRAL program. In B. Meltzer and D. Michie (Eds.), Machine intelligence (Vol. 6, pp. 165–190). Edinburgh: Edinburgh University Press.
18.
Fillmore, C. J. (1968). The case for case. In E. Bach and R. Harms (Eds.), Universals in linguistic theory (pp. 1–88). New York: Holt, Rinehart, and Winston.
19.
Freiherr, G. (1980). The seeds of artificial intelligence (NIH no. 80–2071). Washington, DC: SUMEX-AIM.
20.
Harris, L. R. (1984). Natural language front ends. In P. H. Winston and K. A. Prendergast (Eds.), The AI business (pp. 149–161). Cambridge, MA: MIT Press.
21.
Hayes-Roth, F., Waterman, D. A., and Lenat, D. B. (Eds.). (1983). Building expert systems. Reading, MA: Addison-Wesley.
22.
Hendrix, G. G., Sacerdoti, E. D., Sagalowicz, D., and Slocum, J. (1978). Developing a natural language interface to complex data. ACM Transactions on Database Systems, 8(3).
23.
Hillman, D. J. (1968). Negotiation of inquiries in an online retrieval system. Information Storage and Retrieval, 4, 219–238.
24.
Hillman, D. J. (1973). Customized user services via interactions with LEADERMART. Information Storage and Retrieval, 9, 587–596.
25.
Hillman, D. J. (1981). The feasibility of applying artificial intelligence in the management of C3 networks (Tech. Report STAS Delivery Order No. 1662). Fort Monmouth, NJ: U.S. Army CORADCOM.
26.
Karat, J. (1982). A model of problem solving with incomplete constraint knowledge. Cognitive Psychology, 14, 538–559.
27.
Kidd, A. L. (1983, March 22–25). Human factors in expert systems. Paper presented at the annual conference of the Ergonomics Society, Churchill College, Cambridge, England.
28.
Kraft, A. (1984). XCON: An expert configuration system at Digital Equipment Corporation. In P. H. Winston and K. A. Prendergast (Eds.), The AI business (pp. 41–49). Cambridge, MA: M.I.T. Press.
29.
Lindsay, R. K., Buchanan, B. G., Feigenbaum, E. A., and Lederberg, J. (1980). Applications of artificial intelligence for organic chemistry: The DENDRAL project. New York: McGraw-Hill.
30.
McDermott, J. (1980a). RI: A rule-based configurer of computer systems (Technical Report CMU-CS-80–119). Pittsburgh, PA: Carnegie-Mellon University, Department of Computer Science.
31.
McDermott, J. (1980b). RI: An expert in the computer systems domain. National conference of the American Association of Artificial Intelligence, 1, 269–271.
32.
Michaelis, P. R., Miller, M. L., and Hendler, J. S. (1982). Artificial intelligence and human factors engineering: A necessary synergism in the interface of the future. In A. Badre and B. Schneiderman (Eds.), Directions in humanlcomputer interaction. Norwood, NJ: Ablex.
33.
Moses, J. (1967). Symbolic integration (Report MAC-TR-47). Doctoral dissertation, Dept. of Computer Science, M.I.T., Cambridge, MA.
34.
Muller, F. (1978). Automation. In A. Ralston (Ed.), Encyclopedia of computer science. New York: Van Nostrand Reinhold.
35.
Newell, A. (1980). Physical symbol systems. Cognitive Science, 4, 135–183.
36.
Newell, A., Shaw, J. C., and Simon, H. A. (1960). A variety of intelligent learning in a general problem-solver. In M. C. Yovits and S. Cameron (Eds.), Self-organizing systems (pp. 153–189). New York: Pergamon.
37.
Newell, A., and Simon, H. A. (1963). GPS: A program that simulates human thought. In E. A. Feigenbaum and J. A. Feldman (Eds.), Computers and thought. New York: McGraw-Hill
38.
Peltu, M. (1983). The dangers of fifth generation ballyhoo. Behavior and Information Technology, 2(3), 289–301.
39.
Pople, H. E. (1981). Heuristic methods for imposing structure on ill-structured problems: The structuring of medical diagnostics. In P. Szolovitz (Ed.), Artificial intelligence in medicine. Boulder, CO: Westview Press.
40.
Pople, H. E., Myers, J. D., and Miller, R. A. (1975). DIALOG: A model of diagnostic logic for internal medicine. International Joint Conference on Artificial Intelligence, 4, 848–855.
41.
Rich, R. (1983). Artificial intelligence. New York: McGraw-Hill.
42.
Schank, R. C. (1972). Conceptual dependency: A theory of natural language understanding. Cognitive Psychology, 3, 552–631.
43.
Schank, R. C. (1984). Intelligent advisory systems. In P. H. Winston and K. A. Prendergast (Eds.), The AI business. Cambridge. MA: M.I.T. Press.
44.
Shortliffe, E. H. (1976). Computer-based medical consultation: MYCIN. New York: American Elscvier.
45.
Slagle, J. R. (1961). A heuristic program that solves symbolic integration problems in freshman calculus. Symbolic Automatic Integrator (SAINT) (Report 5G-0001). Cambridge, MA: M.I.T., Lincoln Laboratory.
46.
Van Melle, W. (1979). A domain-independent production rulc system for consultation programs. International Joint Conference on Artificial Intelligence, 6, 923–925.
47.
Winston, P. (1984). Artificial intelligence. Reading, MA: Addison-Wesley.
48.
Woods, W. A. (1970). Transition network grammars for natural language analysis. Communications of the ACM, 13(10), 591–606.
