Efficient Matching Algorithms for the SOAR/OPS5 Production System.

Abstract

SOAR is an problem-solving and learning program intended to exhibit intelligent behavior. SOAR uses a modified form of the OPS5 production system for storage of and access to long-term knowledge. As with most programs which use production systems, the match phase of SOAR's production system dominates all other SOAR processing. This paper describes the results of an investigation of various ways of speeding up the matching process in SOAR through additions and changes to the OPS5 matching algorithm.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1986
Accession Number
ADA174277

Entities

People

  • Daniel J. Scales

Organizations

  • Stanford University

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  • Energy and Power Technologies

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  • Algorithms
  • Artificial Intelligence
  • Buildings And Structures
  • Compilers
  • Computer Programming
  • Computer Science
  • Computers
  • Computing System Architectures
  • Consistency
  • Hash Tables
  • Learning
  • Lists (Data Structures)
  • Machine Languages
  • Parallel Computing
  • Parallel Processing
  • Parallel Processors
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