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The Eighty Five Percent Rule for optimal learning.

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  • 1Department of Psychology, University of Arizona, Tucson, AZ, USA. bob@arizona.edu.

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Learning progresses fastest when training difficulty is optimal, not too easy or hard. The

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Area of Science:

  • Machine Learning
  • Cognitive Science
  • Artificial Intelligence

Background:

  • Optimizing the learning process for humans, animals, and machines is a long-standing challenge.
  • The difficulty of training is a key variable influencing the rate and effectiveness of learning.

Purpose of the Study:

  • To investigate the impact of training difficulty on learning speed across various learning algorithms.
  • To identify the optimal training conditions for efficient learning in binary classification tasks.

Main Methods:

  • Derivation of conditions for an optimal training 'sweet spot' for stochastic gradient-descent algorithms.
  • Analysis of learning algorithms in the context of binary classification problems.

Main Results:

  • A consistent optimal training error rate of approximately 15.87% was identified.
  • This corresponds to an optimal training accuracy of around 85%, termed the 'Eighty Five Percent Rule'.
  • The rule was validated for artificial neural networks (AI) and biologically plausible neural networks.

Conclusions:

  • The 'Eighty Five Percent Rule' provides a quantifiable guideline for optimizing training difficulty.
  • This principle applies to both artificial intelligence and models of animal learning.
  • Adjusting training difficulty to achieve roughly 85% accuracy can accelerate learning.