The present study focused on encoding and retrieval of knowledge as aids to decision-making by comparing the performance of rule-based expert systems and novices' heuristics within the framework of a matching identification problem. A rule-based expert system is developed with a computerized controlled procedure to evaluate and compare its performance with search strategies employed by novices. Analysis indicated that, as problem size increased, the system's outcome compared to novices' heuristics is improved.
Get full access to this article
View all access options for this article.
References
1.
ChiM. T. H.GlazerR.ReesE. (1981) Expertise in problem solving. In SternbergR. J. (Eds), Advances in the psychology of intelligence. Hillsdale, NJ: Erlbaum.
2.
Hayes-RothR.WatermanD. A.LenatD. B. (1983) Building expert systems. Reading, MA: Addison-Wesley.
3.
LarkinJ.McDermottJ.SimonD. P.SimonH. A. (1980) Expert and novice performance in solving physics problems. Science, 208, 1335–1342.
4.
LesgoldA. H.RubinsonH.FeltovichP.GlaserR.KlopferD. (1988) Expertise in complex skills: Diagnosing x-ray pictures. In ChiM. T. H.GlazerR.FarrM. J. (Eds.), The nature of expertise. Hillsdale, NJ: Erlbaum. Pp. 311–342.
5.
MehrezA.SteinbergG. (1995) A matching identification problem: A knowledge engineering approach. ORSA Journal on Computing, 7, 211–131.
6.
TizardB.HughesM. (1984) Young children learning. Cambridge, MA: Harvard Univer. Press.
