The Match Cost of Adding a New Rule: A Clash of Views

Abstract

What is the match cost of adding a new rule to a production system (rule-based system)? Two conflicting views have emerged. Research in EBL indicates that learned rules add to the match cost of a production system. Thus, as the production system size increases with learning, the match cost will also increase. There is much data in the literature to support this phenomenon. On the contrary, researchers in parallel production systems have concluded that the match effort in a production system is limited, independent of the size of the production system. Thus, an increase in the size of the production system will not lead to an increase in the match cost. There is much data to support this phenomenon as well. In this paper, we point out these contradictory views of production match in the two research communities. A direct analysis of these conflicting views is difficult, since the two communities have worked with vastly different systems. Therefore, we have developed some large production systems in Soar, to analyze the situation within a common framework. This common framework narrows down the possible causes for this conflict, and raises important questions for future work.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1992
Accession Number
ADA253971

Entities

People

  • Allen Newell
  • Milind Tambe
  • Robert Doorenbos

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Automata Theory
  • Computations
  • Computer Programming
  • Computer Science
  • Computers
  • Computing System Architectures
  • Expert Systems
  • Knowledge Based Systems
  • Learning
  • Machine Learning
  • Parallel Computing
  • Parallel Processing
  • Production
  • Rule Based Systems
  • Universities

Readers

  • Artificial Intelligence
  • Economics