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Neural Networks and the Philosophy of Dialectical Positivism

Suleimenov Ibragim, Massalimova Aliya, Bakirov Akhat and 1 more

MATEC Web of Conferences · 2018

doi:10.1051/matecconf/201821402002 (opens in a new tab)

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Abstract

The fact that the theory of neural networks permits the completeness of the concept of global evolutionism has been shown. This concept in the current philosophical literature is seen, inter alia, as an effective platform for interdisciplinary cooperation, the need for which is becoming more acute, which is reflected in the anniversary report of the Club of Rome in the form of the thesis on the “New Enlightenment”. The theory of neural networks allows us to give a consistent interpretation of the category of “complex”, in accordance with which a system of arbitrary nature is treated as “complex” if it is possible to indicate a complementary analog of a neural network. With this interpretation, the evolution of systems of an arbitrary nature can indeed be described in a uniform way. In particular, the philosophical law of transition from quantity to quality can be reduced to a description in terms of information theory (through the description of the evolution of a neural network complementary to a complex system). The main result of the work is a new interpretation of the dialectical philosophy categorical apparatus on the basis of the theory of neural networks.

Abstract licence: CC BY

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