Parse Completion: A Study of an Inductive Domain

Abstract

Hierarchical knowledge structures are pervasive in Artificial Intelligence, yet very little is understood about how such structures may be effectively acquired. One way to represent the hierarchical component of knowledge structures is to use grammars. The grammar framework also provides a natural way to apply failure-driven learning to guide the induction of hierarchical knowledge structures. The conjunction of hierarchical knowledge structures and failure-driven learning defines a class of algorithms, which we call Parse Completion algorithms. This paper presents a theoretical exploration of this class that attempts to understand what makes this induction problem difficult, and to suggest where appropriate biases might lie to limit the search without overly restricting the richness of discoverable solutions. The explorations in this paper are not intended to produce a practical induction algorithm, although fruitful paths for such development are suggested. (sdw)

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1987
Accession Number
ADA222322

Entities

People

  • Steve Nowlan

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Alphabets
  • Applied Computer Science
  • Artificial Intelligence
  • Automata
  • Classification
  • Computer Languages
  • Computer Science
  • Construction
  • Context Free Grammars
  • Grammars
  • Guarantees
  • Hierarchies
  • Language
  • Machine Learning
  • Production
  • Trees (Data Structures)

Fields of Study

  • Computer science

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms