BIB-VERSION:: CS-TR-v2.0
          ID:: STAN//CS-TR-87-1175
       ENTRY:: April 24, 1995
ORGANIZATION:: Stanford University, Department of Computer Science
       TITLE:: Using and Evaluating Differential Modeling in Intelligent
               Tutoring and Apprentice Learning Systems
        TYPE:: Technical Report
      AUTHOR:: Wilkin, D. C.
        DATE:: January 1987
       PAGES:: 32
    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 againt 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 terrns of the knowledge
               representation and control language constructs of the expert
               system.
       NOTES:: [Adminitrivia V1/Prg/19950424]
         END:: STAN//CS-TR-87-1175