Less than general production system architectures

  • Authors:
  • Douglas B. Lenat;John McDermott

  • Affiliations:
  • Carnegie-Mellon University, Pittsburgh, PA;Carnegie-Mellon University, Pittsburgh, PA

  • Venue:
  • IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
  • Year:
  • 1977

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Abstract

Many of the recent expert rule-based systems [Dendral, Mycin, AM, Pecos] have architectures that differ significantly from the simple domain-independent architectures of "pure" production systems. The purpose of this paper is to explore, somewhat more systematically than has been done before, the various ways in which the simplicity constraints can be relaxed, and the benefits of doing so. The most significant benefits arise from three sources: (i) the grain size of a typical rule can be increased until it captures a unit of advice which is meaningful in that system's task domain, (ii) the interpreter can become accessible to the rules and thus become dynamically modifiable, and (iii) meaningful permanent Knowledge can be stored in data memories, not just within productions. Although there are costs associated with relaxing the simplicity constraints, for many task domains the benefits outweigh the costs.