A knowledge-based framework for learning, applying and consulting engineering procedures
A knowledge-based framework called LACEPRO where civil engineers are able to learn, consult and apply established procedures is presented. LACEPRO's knowledge base was designed to be used by three different knowledge operators: the Tutor, the Consultor, and the Expert. Each of these knowledge operators has its own mechanisms to perform their functions over the shared knowledge base. The core of the knowledge base is a set of networks which represent the steps of the engineering procedures. They function as a platform for: teaching procedures, automatic problem generation, diagnosis of user's misunderstandings, problem solving, consultation, and user's navigation through the domain knowledge.
Unable to display preview. Download preview PDF.
- 1.Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Mateo, CA (1988).Google Scholar
- 2.Carbonell, J.R.: AI in CAI: an artificial intelligence approach to computer-assisted instruction. IEEE Transactions of Man-Machine Systems 11(4) (1970) 190–202.Google Scholar
- 3.Barr, A., Beard, M., Atkinson, R.C.: The computer as a tutorial laboratory: the Stanford BIP Project. International Journal of Man-Machine Studies 8 (1976) 567–596.Google Scholar
- 4.Goldstein, I.P.: The genetic graph: a representation for the evolution of procedural knowledge, in Proceedings of the Second Annual Conference of the Canadian Society for Computational Studies of Intelligence, Toronto, (1978) 100–106.Google Scholar
- 5.Lesgold, A.M., Bonar, J.G., Bowen, A.: An intelligent tutoring system for electronics troubleshooting: DC-circuit understanding. Technical Report. Learning Research and Development Center, University of Pittsburgh, Pennsylvania (1987).Google Scholar
- 6.Bonar, J.G., Cunningham R., Schultz, J: An object-oriented architecture for intelligent tutoring systems, in Proceedings of the ACM Conference on Object-oriented Programming systems, Languages and Applications, New York, USA (1986).Google Scholar
- 7.Scott, P., Ryu, J.: An Intelligent tutorial system for computer aided architectural design, in Proceedings of Artificial Intelligence in Design'91, Edinburgh, UK, Butterworth-Heinemann, (1991) 331–46.Google Scholar
- 8.Brown, J.S., Burton, R.R.: Diagnostic models for procedural bugs in basic math-ematical skills, Cognitive Science 3 (1978) 155–191.Google Scholar
- 9.Acker, L., Porter, B.: Extracting viewpoints from knowledge bases. In Proceedings of AAAI-94 (1994).Google Scholar
- 10.Fikes R., Gruber T., Iwasaki Y., Levy A., Nayak, P.: How things work project overview, Knowledge Systems Laboratory Technical Report KSL-91-70, Computer science Department, Stanford University, USA, November (1991).Google Scholar
- 11.López, A., Vilar, I., Muñoz, C., Alanís, A., De Buen P.: Manual de diseño por viento, Comisión Federal de Electricidad, CFE-IIE, México (1993).Google Scholar