挖掘人工意识多维度的粗糙集&黎曼协方差矩阵理论

Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2020-06-30 DOI:10.1145/3405962.3405974

Rory A. Lewis

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引用次数: 1

摘要

本文提出了一种利用粗糙集理论和黎曼协方差矩阵分析人类意识与大脑相互作用时的多维性的方法。我们从数学上定义了运行人工意识的机器人操作系统的婴儿状态，它的人工智能和运动功能与操作系统相互排斥。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Rough Set & Riemannian Covariance Matrix Theory for Mining the Multidimensionality of Artificial Consciousness

This paper presents a means to analyze the multidimensionality of human consciousness as it interacts with the brain by utilizing Rough Set Theory and Riemannian Covariance Matrices. We mathematically define the infantile state of a robot's operating system running artificial consciousness, which operates mutually exclusively to the operating system for its AI and locomotor functions.

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Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics

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