Accession Number : ADA187503
Title : Using and Evaluating Differential Modeling in Intelligent Tutoring and Apprentice Learning Systems.
Descriptive Note : Technical rept.,
Corporate Author : STANFORD UNIV CA DEPT OF COMPUTER SCIENCE
Personal Author(s) : Wilkins, David C ; Clancey, William J ; Buchanan, Bruce G
PDF Url : ADA187503
Report Date : Jan 1987
Pagination or Media Count : 41
Abstract : A powerful approach to debugging and refining the knowledge structures of a problem solving agent is to differentially model the actions of the agent against a gold standard. This paper proposes a framework for exploring the inherent limitations of such an approach when a problem solver is differentially modeled against an expert system. A procedure is described for determining a performance upper bound for debugging via differential modeling, called the synthetic agent method. The synthetic agent method systematically explores the space of near miss training instances and expresses the limits of debugging in terms of the knowledge representation and control language constructs of the expert system. Keywords: Learning, Knowledge acquisition, Tutoring, Debugging, Differential modeling.
Descriptors : *DEBUGGING(COMPUTERS), *LEARNING, *TEACHING METHODS, *APPRENTICESHIP, *INSTRUCTIONAL MATERIALS, CONTROL, LANGUAGE, MODELS, PROBLEM SOLVING
Subject Categories : Humanities and History
Distribution Statement : APPROVED FOR PUBLIC RELEASE