System Engineering Techniques for Artificial Intelligence Systems

Abstract

It is impossible to develop a large knowledge-based artificial intelligence system successfully without careful attention to issues of system engineering. A set of principles is presented for organizing the design and implementation of such a system. Problems of maintainability and configuration control, human engineering, performance analysis, and efficiency must be faced. Tools used to solve these problems are described, along with examples of their use in the Hearsay-II speech understanding system.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1977
Accession Number
ADA056067

Entities

People

  • Lee D. Erman
  • Victor R. Lesser

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Air Force
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Automated Speech Recognition
  • Complex Systems
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Engineering
  • Grammars
  • Human Factors Engineering
  • Knowledge Based Systems
  • Language
  • Operating Systems
  • Universities
  • Vocabulary

Fields of Study

  • Computer science
  • Engineering

Readers

  • Speech Processing/Speech Recognition.
  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

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