Knowledge Acquisition from Structural Descriptions

Abstract

The representation of concepts and antecedent-consequent productions is discussed and a method for inducing knowledge by abstracting such representations from a sequence of training examples is described. The proposed learning method, interference matching, induces abstractions by finding relational properties common to two or more exemplars. Three tasks solved by a program which performs an interference matching algorithm are presented. Several problems concerning the relational representation of examples and the induction of knowledge by interference matching are also discussed.

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Document Details

Document Type
Technical Report
Publication Date
Feb 11, 1976
Accession Number
ADA025074

Entities

People

  • Frederick Hayes-roth
  • John Mcdermott

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acquisition
  • Air Force
  • Algorithms
  • Artificial Intelligence
  • Computer Science
  • Concept Formation
  • Construction
  • Grammars
  • Identification
  • Language
  • Learning Machines
  • Machine Learning
  • New York
  • Pattern Recognition
  • Recognition
  • Training
  • Transformational Grammars

Readers

  • Artificial Intelligence