Integrating Multiple Sources of Knowledge into Designer-Soar, an Automatic Algorithm Designer

Abstract

Designing algorithms requires diverse knowledge about general problem-solving, algorithm design, implementation techniques, and the application domain. The knowledge can come from a variety of sources, including previous design experience, and the ability to integrate knowledge from such diverse sources appears critical to the success of human algorithm designers. Such integration is feasible in an automatic design system, especially when supported by the general problem-solving and learning mechanisms in the Soar architecture. Our system, Designer-Soar, now designs several simple generate-and-test and divide-and-conquer algorithms. The system already uses several levels of abstraction, generalizes from examples, and learns from experience, transferring knowledge acquired during the design of one algorithm to aid in the design of others. Keywords: Reprints; Symposia; Proceedings; Algorithm design; Weak methods; Knowledge; Soar; Designer-soar; Artificial intelligence.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1988
Accession Number
ADA219117

Entities

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  • Allen Newell
  • David Steier

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  • Carnegie Mellon University

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  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
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  • AI & ML
  • AI & ML - Machine Learning Algorithms