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Can We Learn Algorithms from People Who Compute Fast: An Indirect Analysis in the Presence of Fuzzy Descriptions

  • Olga Kosheleva
  • Vladik Kreinovich
Chapter
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 273)

Abstract

In the past, mathematicians actively used the ability of some people to perform calculations unusually fast. With the advent of computers, there is no longer need for human calculators - even fast ones. However, recently, it was discovered that there exist, e.g., multiplication algorithms which are much faster than standard multiplication. Because of this discovery, it is possible than even faster algorithm will be discovered. It is therefore natural to ask: did fast human calculators of the past use faster algorithms - in which case we can learn from their experience - or they simply performed all operations within a standard algorithm much faster? This question is difficult to answer directly, because the fast human calculators’ self description of their algorithm is very fuzzy. In this paper, we use an indirect analysis to argue that fast human calculators most probably used the standard algorithm.

Keywords

Fuzzy Logic Fast Algorithm Inverse Fourier Transform Standard Algorithm Time Ratio 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Olga Kosheleva
    • 1
  • Vladik Kreinovich
    • 2
  1. 1.University of Texas at El PasoEl PasoUSA
  2. 2.Department of Computer ScienceUniversity of Texas at El PasoEl PasoUSA

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