CONSENSUS: A Statistical Learning Procedure in a Connectionist Network.

Abstract

This document presents a new scheme for the activity of neuron-like elements in a connectionist network. The CONSENSUS (Context Sensitive Networks Using Statistics), is that decisions should be deferred until sufficient evidence accumulates to make an informed choice. Consequently, large changes in network structure can be made with confidence. Nodes have an awareness of their role and utility in the network which allows them to increase their effectiveness. The reinforcement scheme utilizes the notion of confidence so that only nodes proven to contribute successfully issue reinforcements. Nodes are grouped into communities to exploit their collective knowledge which exceeds any individual member. The network was tested against several problems and was able to find suitable encodings to solve them.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1987
Accession Number
ADA188531

Entities

People

  • Gordon J. Goetsch

Organizations

  • Carnegie Mellon University

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Aeronautical Laboratories
  • Air Force
  • Availability
  • Boundaries
  • Classification
  • Computations
  • Computer Science
  • Computers
  • Information Processing
  • Information Science
  • Neural Networks
  • Pattern Recognition
  • Probability
  • Security
  • Statistical Inference
  • Statistics

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.
  • Regression Analysis.