Synergetics of artificial cognitive systems nonequilibrium stability

Andrei Armovich Gribkov, Aleksandr A. Zelenskii
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Abstract

The article explores a set of issues determining the synergetics of artificial cognitive systems: conditions for the realization of non-equilibrium stability of systems, synthesis options of artificial cognitive system, as well as mechanisms of self-organization of consciousness formed on its basis. Artificial cognitive systems are proposed to include not only artificial intelligence systems imitating human thinking, but any multilevel systems that perform the functions of recognizing and remembering information, decision-making, storage, explanation, understanding and production of new knowledge. The defining property of a cognitive system is the ability to make decisions. It is shown that the content of the cognitive system is consciousness, interpreted within the framework of the information concept as an information environment in which the extended model of reality is realized. Consciousness can be qualified as an open dynamic system. The state of such systems is determined by the processes occurring in them (thought processes - in the case of consciousness). For such systems, called "living", there is a realization of mechanisms of stable disequilibrium. The implementation of an artificial cognitive system is technically carried out on the basis of an artificial neural network, and organizationally - according to the actor or reactor model. Self-organization processes determining the synergetics of consciousness are a special case of the extreme principle, which is a consequence of the law of excessive reaction of supersystems, regulating the existence of dissipative systems at the expense of supersystem resources. The initiation of self-organization of consciousness is carried out by the process of thinking, which, due to the non-equilibrium stability of consciousness, does not stop. Thus thinking can be interpreted as a process of varying system parameters in search of suitable ones for extended modeling of reality.
人工认知系统非平衡稳定性的协同作用
文章探讨了决定人工认知系统协同性的一系列问题:实现系统非平衡稳定性的条件、人工认知系统的合成选项以及在其基础上形成的意识自组织机制。我们提出的人工认知系统不仅包括模仿人类思维的人工智能系统,还包括任何具有识别和记忆信息、决策、存储、解释、理解和产生新知识等功能的多层次系统。认知系统的决定性属性是决策能力。研究表明,认知系统的内容是意识,在信息概念的框架内被解释为实现现实扩展模型的信息环境。意识可以说是一个开放的动态系统。这种系统的状态由其中发生的过程(思想过程--就意识而言)决定。对于这种被称为 "生命 "的系统来说,稳定的不平衡机制是可以实现的。人工认知系统的实现在技术上以人工神经网络为基础,在组织上则根据行为者或反应者模式。决定意识协同的自组织过程是极端原则的一个特例,它是超系统过度反应规律的结果,以牺牲超系统资源为代价调节耗散系统的存在。意识自组织的启动是通过思维过程进行的,由于意识的非平衡稳定性,思维过程不会停止。因此,思维可以解释为一个改变系统参数的过程,以寻找合适的参数来扩展现实模型。
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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