Abstract
The San Bernardino National Forest in southern California has recently developed a systematic approach to wildfire prevention planning. However, a comprehensive document or other mechanism for teaching this process to other prevention personnel does not exist. Anintelligent tutorial expert system is being constructed to provide a means for learning the process and to assist in the creation of specific prevention plans. An intelligent tutoring system (ITS) contains two types of knowledge—domain and tutoring. The domain knowledge for wildfire prevention is structured around several foci: (1) individual concepts used in prevention planning; (2) explicitly specified interrelationships between concepts; (3) deductive methods that contain subjective judgment normally unavailable to less-experienced users; (4) analytical models of fire behavior used for identification of hazard areas; (5) how-to guidance needed for performance of planning tasks; and (6) expository information that provides a rationale for planning steps and ideas. Combining analytical, procedure, inferential, conceptual, and expositional knowledge into a tutoring environment provides the student and/or user with a multiple perspective of the subject matter. Aconcept network provides a unifying framework for structuring and utilizing these diverse forms of prevention planning knowledge. This network structure borrows from and combines semantic networks and frame-based knowledge representations. The flexibility of this organization facilitates an effective synthesis and organization of multiple knowledge forms.
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Literature cited
Anderson, J. R., and B. J. Reiser. 1985. The LISP tutor.BYTE 10 (4): 159–175.
Anderson, J. R., C. Boyle, and C. Yost. 1985. The geometry tutor. Pages 245–251in A. K. Lochi (ed.) Proceedings of the ninth Los Angeles, CA international joint conference on artificial intelligence, William Kaufmann, Los Altos, CA.
Andrews, P. L. 1986. BEHAVE: Fire behavior prediction and fuel modeling system—BURN subsystem. USDA Forest Service General Technical Report INT-194. Intermountain Research Station, Ogden, Utah. 130 pp.
Barr, A., and E. A. Feigenbaum. 1981. The handbook of artificial intelligence, volume 1. William Kaufmann, Los Altos, California. 409 pp.
Bradshaw, W. G., and R. Johnson. 1989. Fire prevention planning: fire loss reduction.Fire Technology (in press).
Clancey, W. J. 1987. Knowledge-Based tutoring: The GUIDON program. The MIT Press, Cambridge, Massachusetts. 377 pp.
Clancey, W. J., and R. Letsinger. 1981. NEOMYCIN; Reconfiguring a rule-based expert system for application to teaching. Pages 361–381in W.J. Clancey and E. H. Shortliffe (eds.), Readings in medical artificial intelligence: The first decade, Addison-Wesley, Reading, Massachusetts.
Davis, R., B. G. Buchanan, and E. H. Shortliffe. 1977. Production rules as a representation for a knowledge-base consultation program.Artificial Intelligence 8(1): 15–45.
Duda, R. O., P. E. Hart, N.J. Nilsson, and G. L. Sutherland. 1978. Semantic network representations in rule-based inference systems. Pages 203–221in D. A. Waterman and F. Hayes-Roth (eds.), Pattern-directed inference systems. Academic Press, New York.
Gale, R. D. 1977. Evaluation of fire management activities on the national forests. Policy Analysis Staff Report, USDA Forest Service, Washington DC. 127 pp.
Hayward, S.A., B.J. Wielinga, and J. A. Breuker. 1986. Structured analysis of knowledge. Pages 18-0–18-7in J. H. Boose and B. R. Gaines (eds.), Proceedings of the knowledge acquisition for knowledge-based systems workshop. Boeing Computer Services, Seattle, Washington.
Imlah, W., and B. du Boulay. 1985. Robust natural language parsing in computer assisted language instruction.Systems 13(2):115–127.
Johnson, W. L. and E. Soloway. 1985. PROUST.BYTE 10(4): 179–190.
Kolbe, R. W., R. H. Gattis, Jr., and M. F. Augusteijn. 1987. Special-purpose deduction techniques for intelligent tutoring systems. Pages 143–151in M.J. Defries (ed.), Proceedings of the second annual Rocky Mountain conference on artificial intelligence. Colorado Institute for Artificial Intelligence, Boulder, Colorado.
Minsky, M. 1975. A framework for representing knowledge. Pages 211–277in P. Winston (ed.), The psychology of computer vision. McGraw-Hill, New York.
O'Hare, G. M., and D. A. Bell. 1985. The coexistence approach to knowledge representation.Expert Systems 2(4):230–238.
Oliver, A. E. M. 1986. Control of rapid prototyping in expert systems development. Pages 247–252in Second international expert systems conference. Learned Information, Oxford.
Quillian, M. R. 1968. Semantic memory. Pages 227–270in M. Minsky (ed.), Semantic information processing. The MIT Press, Cambridge, Massachusetts.
Reinhardt, E. 1987. An expert system for designing fire prescriptions. Pages 223–225in J. B. Davis and R. E. Martin (eds.), Proceedings of the symposium on wildland fire 2000. General Technical Report PSW-101 Berkeley, California. Pacific Southwest Forest and Range Experiment Station, Forest Service, US Department of Agriculture.
Schank, R. C., and R. P. Abelson. 1977. Script, plans, and goals and understanding. Lawrence Erlbaum, Hillsdale, New Jersey.
Schmoldt, D. L. 1987a. Implementing design considerations in a forest pest diagnosis expert system.In M. G. Gaffney (ed.), Proceedings of the first annual conference on INSIGHT/LEVEL5 expert system applications. USERS.PRL, Ramsey, New Jersey. 15 pp.
Schmoldt, D. L. 1987b. Evaluation of an expert system approach to pest management of Wisconsin red pine (Pinus resinosa). PhD dissertation. University Microfilms International, 225 pp.
Schmoldt, D. L., and W. G. Bradshaw. 1988. A cumulative Delphi approach to knowledge acquisition. Pages 149–162in Y. Wilks (ed.), Proceedings of the third annual Rocky Mountain conference on artificial intelligence. Rocky Mountain Society for Artificial Intelligence, Denver, Colorado.
White, B. Y., and J. R. Frederiksen. 1986. Intelligent tutoring systems based upon qualitative model evolutions. Pages 313-326in Proceedings of AAAI-86, fifth national conference on artificial intelligence. Morgan Kaufmann, Los Altos, California.
Woolf, B., D. Blegen, J. H. Jansen, and A. Verloop. 1986. Teaching a complex industrial process. Pages 722–728in Proceedings of AAAI-86, fifth national conference on artificial intelligence. Morgan Kaufmann, Los Altos, California.
Yazdani, M. 1986. Intelligent tutoring systems: An overview.Expert Systems 3(3): 154–160.
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Schmoldt, D.L. Organizing knowledge for tutoring fire loss prevention. Environmental Management 13, 573–582 (1989). https://doi.org/10.1007/BF01874963
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DOI: https://doi.org/10.1007/BF01874963