THE INSTRUCTIBLE PRODUCTION SYSTEM: A RETROSPECTIVE ANALYSIS

In building systems that acquire knowledge from tutorial instruction, progress depends on determining certain functional requirements and ways for them to be met. The Instructible Production System (IPS) project has explored learning by building a series of experimental systems. These systems can be viewed as being designed to explore the satisfaction of some of the requirements, both by basic production system mechanisms and by features explicitly programmed as rules. The explorations have brought out the importance of considering in advance (as part of the kernel design) certain functional components rather than having them be filled in by instruction. The need for the following functional components has been recognized: interaction language organization of procedural elements explanation of system behavior accommodation to new knowledge connection of goals with system capabilities reformulation (mapping) of knowledge evaluation of behavior compilation to achieve efficiency and automaticity Since the experimental systems have varied in their effectiveness, some general conclusions can be drawn about the relative merits of various approaches. Seven such approaches are discussed here, with particular attention to the three whose behavior can be most effectively compared, and which reflect the temporal development of the project.

[1]  David Jechiel Mostow,et al.  Mechanical transformation of task heuristics into operational procedures , 1981 .

[2]  H A Simon,et al.  The theory of learning by doing. , 1979, Psychological review.

[3]  McDermott ANA : an assimilating and accommodating production system , 1978 .

[4]  John P. McDermott,et al.  OPS, A Domain-Independent Production System Language , 1977, IJCAI.

[5]  Allen Newell,et al.  Human Problem Solving. , 1973 .

[6]  Michael David Rychener,et al.  Production systems as a programming language for artificial intelligence applications. , 1976 .

[7]  Allan Collins Explicating the Tacit Knowledge in Teaching and Learning. Technical Report No. 5. , 1978 .

[8]  Michael D. Rychener,et al.  A Semantic Network of Production Rules in a System for Describing Computer Structures , 1979, IJCAI.

[9]  Allen Newell,et al.  An instructable production system: basic design issues , 1977, SGAR.

[10]  Victor R. Lesser,et al.  A Retrospective View of the Hearsay-II Architecture , 1977, IJCAI.

[11]  J. McDermott,et al.  Production system conflict resolution strategies , 1977, SGAR.

[12]  Charles L. Forgy OPS4 user's manual , 1979 .

[13]  Michael D. Rychener Control requirements for the design of production system architectures , 1977 .

[14]  J. Flavell Metacognitive aspects of problem solving , 1976 .

[15]  Tom M. Mitchell,et al.  Models of Learning Systems. , 1979 .

[16]  John R. Anderson,et al.  A Theory of the Acquisition of Cognitive Skills. , 1978 .

[17]  John R. Anderson Language, Memory, and Thought , 1976 .

[18]  Allen Newell,et al.  How can Merlin understand , 1973 .

[19]  Charles Lanny Forgy,et al.  On the efficient implementation of production systems. , 1979 .

[20]  Donald A Waterman Rule-Directed Interactive Transaction Agents: An Approach to Knowledge Acquisition. , 1978 .

[21]  Michael D. Rychener The Student Production System: A Study of Encoding Knowledge in Production Systems , 1975 .

[22]  Allen Newell,et al.  AN INSTRUCTABLE PRODUCTION SYSTEM: BASIC DESIGN ISSUES1 , 1978 .

[23]  C. Forgy,et al.  PRODUCTION SYSTEM CONFLICT RESOLUTION STRATEGIES1 , 1978 .