通往机器意识之路:识别物质对象的隐藏系统属性

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
V. A. Zhebit
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引用次数: 0

摘要

如果不了解反映机器特殊属性的规律,就不可能找到人工智能机器的方法。现有的概念和规律基础已不能满足现代要求,需要进行扩展。这些任务符合理论分析的计划方向,其目的是确定物理对象的隐藏系统属性。本文提出了新的方法论,从而有可能找出物理对象相互作用中反映因果关系的一些隐藏机制。新出现的方法论以制定的定律不完备性原则为基础,与现有的数理逻辑规定相辅相成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Way to Machine Consciousness: Identification of Hidden System Properties of Material Objects

The search for approaches to machines with artificial intelligence is impossible without understanding the laws reflecting their special properties. The existing base of concepts and laws no longer meets modern requirements and requires expansion. These tasks correspond to the planned direction of theoretical analysis, which aims to identify the hidden system properties of physical objects. New methodological approaches are presented, which made it possible to identify some hidden mechanisms reflecting cause-and-effect relationships in the interactions of physical objects. The emerging new methodology is based on the formulated principle of the incompleteness of laws, which is complementary to the existing provisions of mathematical logic.

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来源期刊
AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS
AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-
自引率
40.00%
发文量
18
期刊介绍: Automatic Documentation and Mathematical Linguistics  is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.
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