THEORY OF PROBABILITY STATE VARIABLE SYSTEMS, VOLUME VI: PERCEPTION, DECISION-MAKING, AND ACTION.

Abstract

This report discusses approaches whereby Neurotron Networks can be used to provide pattern recognition, autonomous decision-making, and action. The intent is to illustrate the versatility of Neurotron networks, and their potential application to actual problems, and to provide a framework for the mathematical studies of PSV systems. To illustrate pattern recognition, an artificial fovea with jitter analogous to the human eye is described, and how this, together with a Neurotron network, can learn to assign meaning to symbols, including the ability to learn to recognize handprinted letters. To illustrate autonomous decision-making, it is shown how a Neurotron network can develop its own strategy for playing chess. To illustrate action, it is shown how a Neurotron network can learn to control an arm and hand with visual, tactile, and kinesthetic feedback, and it is shown how a Neurotron network can learn to drive suitable output devices to mimic a simple tune. (Author)

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1963
Accession Number
AD0427771

Entities

People

  • R. J. Lee

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Feedback
  • Identification
  • Pattern Recognition
  • Perception
  • Probability
  • Recognition

Readers

  • Neural Network Machine Learning.
  • Robotics and Automation.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks