Function Learning: An Exemplar Account of Extrapolation Performance

Abstract

A function describes a one-to-one relationship between combinations of predictor and criterion variables. In this paper, we describe a new memory model that learns functional relationships. Two versions of the model are described. The first version learns the bivarite relationship between a single predictor and criterion. The second version expands on the first to multiple predictors. For both versions of the model, we present empirical data to test them and find that they do a good job of accounting for human performance.

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Document Details

Document Type
Technical Report
Publication Date
Oct 29, 2003
Accession Number
ADA593833

Entities

People

  • Andrew Neal
  • Peter J. Kwantes

Organizations

  • Defence Research and Development Canada

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Abstracts
  • Accounting
  • Air Temperature
  • Aircrafts
  • Boundaries
  • Equations
  • Exponential Functions
  • Extrapolation
  • Helicopters
  • Learning
  • Mathematical Analysis
  • Motor Skills
  • National Security
  • Psychological Phenomena And Processes
  • Psychology
  • Trainees
  • Training

Fields of Study

  • Psychology

Readers

  • Computational Modeling and Simulation
  • Neural Network Machine Learning.
  • Regression Analysis.