Human and computer learning: An experimental study

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Simple memorizing tasks have been chosen such as a binary code on a matrix. After the establishment of an appropriate protocol, the codified matrices were individually presented to 150 university students who had to memorize them. A computer simulation for a similar task is available which uses a perceptron on which an algorithm was implemented allowing for some degree of globality (technically referred to as entropic nonextensivity within a current generalization of the usual, Boltzmann-Gibbs, statistical mechanics). Our main observation is that, for the very specific learning task on which we focus here, humans perform similarly to slightly nonextensive perceptrons.
To appear in Complexus (Karger, Basel). 9 pages including 12 figures

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