Can mathematics explain natural intelligence?
type: Item
instance of: scholarly article
title: Can mathematics explain natural intelligence?
zbMATH Open document ID: 0611.92031
DOI: 10.1016/0167-2789(86)90307-3
author: Jan Mycielski
published in: Physica D
publication date: 1986-01-01T00:00:00Z
review text: I discuss four algorithms that have one thing in common with the brain: they learn to predict future events based on past experience. The first is the classical predictor \(\hat x_{t+h}=3x_ t-3x_{t-h}+x_{t-2h}\) for the values of a quadratic progression. The second predicts the values of linear functionals. The third predicts the vector outputs of an orthogonal operator. The fourth predicts the letters or morphemes of a text. The first, second, and fourth are simple enough so that mechanisms appropriate for the computations that they require could exist in our brains. I prove estimates of the sum of the absolute squares of errors for the second and third algorithm.
Mathematics Subject Classification ID: 91E30
Mathematics Subject Classification ID: 62M20
zbMATH DE Number: 3989171
zbMATH Keywords: intelligence
zbMATH Keywords: prediction
zbMATH Keywords: algorithms
zbMATH Keywords: brain
zbMATH Keywords: past experience
zbMATH Keywords: quadratic progression
zbMATH Keywords: linear functionals
zbMATH Keywords: orthogonal operator
zbMATH Keywords: letters
zbMATH Keywords: morphemes
zbMATH Keywords: estimates of the sum of the absolute squares of errors
MaRDI profile type: Publication
full work available at URL: 0167-2789(86)90307-3
OpenAlex ID: W2082068414
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description: scientific article; zbMATH DE number 3989171