A Model for Learning Systems

Abstract

A model for learning systems is presented, and representative AI, pattern recognition, and control systems are discussed in terms of its framework. The model details the functional components felt to be essential for any learning system, independent of the techniques used for its construction, and the specific environment in which it operates. These components are performance element, instance selector, critic, learning element, blackboard, and world model. Consideration of learning system design leads naturally to the concept of a layered system, each layer operating at a different level of abstraction.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1977
Accession Number
ADA042834

Entities

People

  • Bruce G. Buchanan
  • Reid G. Smith
  • Richard A. Chestek
  • Tom M. Mitchell

Organizations

  • Stanford University

Tags

Communities of Interest

  • Autonomy
  • Biomedical

DTIC Thesaurus Topics

  • Adaptive Control Systems
  • Adaptive Systems
  • Artificial Intelligence
  • Computer Programming
  • Computer Science
  • Computers
  • Construction
  • Control Systems
  • Environment
  • Governments
  • Machine Learning
  • Mass Spectrometry
  • Pattern Recognition
  • Psychology
  • Recognition
  • Self Organizing Systems
  • United States

Readers

  • Artificial Intelligence
  • Software Engineering

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks