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Neural Networks and the Philosophy of Dialectical Positivism

机译:神经网络与辩证实证主义哲学

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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.
机译:已经证明了神经网络理论可以使全球进化论的概念完整。在当前的哲学文献中,这一概念尤其被视为跨学科合作的有效平台,对此的需求日益迫切,这反映在罗马俱乐部周年纪念报告中,其主题是“新启蒙”。神经网络的理论使我们能够对“复杂”的类别给出一致的解释,根据该解释,如果可能表示神经网络的互补类似物,则将任意性质的系统视为“复杂”。通过这种解释,可以用统一的方式描述任意性质的系统的演化。特别地,从数量到质量的转变的哲学定律可以简化为信息论的描述(通过对与复杂系统互补的神经网络的演化进行描述)。这项工作的主要成果是在神经网络理论的基础上对辩证哲学分类仪器的新解释。

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