Actor modeling of real-time cognitive systems: ontological basis and software-mathematical implementation

A. A. Zelenskii, Andrei Armovich Gribkov
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Abstract

The article is devoted to the study of the problem of increasing the reliability of modeling of cognitive systems, to which the authors refer not only human intelligence, but also artificial intelligence systems, as well as intelligent control systems for production, technological processes and complex equipment. It is shown that the use of cognitive systems for solving control problems causes very high rapidity requirements for them. These requirements combined with the necessity to simplify modeling methods as the modeling object becomes more complex determine the choice of an approach to modeling cognitive systems. Models should be based on the use of simple algorithms in the form of trend detection, correlation, as well as (for solving intellectual problems) on the use of algorithms based on the application of various patterns of forms and laws. In addition, the models should be decentralized. An adequate representation of decentralized systems formed from a large number of autonomous elements can be formed within the framework of agent-based models. For cognitive systems, two models are the most elaborated: actor and reactor models. Actor models of cognitive systems have two possible realizations: as an instrumental model or as a simulation. Both implementations have the right to exist, but the possibilities of realizing a reliable description when using the tool model are higher, because it provides incommensurably higher rapidity, and also assumes variability of the modeled reality. The actor model can be realized by means of a large number of existing programming languages. The solution to the problem of creating simulative actor models is available in most languages that work with actors. Realization of instrumental actor models requires rapidity, which is unattainable in imperative programming. In this case, the optimal solution is to use actor metaprogramming. Such programming is realizable in many existing languages.
实时认知系统的行动者建模:本体论基础和软件数学实现
本文致力于研究提高认知系统建模可靠性的问题,作者所指的认知系统不仅包括人类智能,还包括人工智能系统,以及生产、技术过程和复杂设备的智能控制系统。研究表明,使用认知系统解决控制问题对其快速性要求非常高。这些要求加上随着建模对象变得越来越复杂而简化建模方法的必要性,决定了认知系统建模方法的选择。模型应基于使用趋势检测、相关性等形式的简单算法,以及(用于解决智力问题的)基于应用各种形式和规律的算法。此外,模型应该是分散的。在基于代理的模型框架内,可以充分代表由大量自主元素组成的分散系统。对于认知系统而言,有两种模型最为详尽:行动者模型和反应者模型。认知系统的行为体模型有两种可能的实现方式:工具模型或模拟。这两种实现方式都有存在的权利,但使用工具模型时,实现可靠描述的可能性更高,因为它提供了不可比拟的更快速度,而且还假定了模型现实的可变性。演员模型可以通过大量现有的编程语言来实现。大多数使用行为体的语言都可以解决创建模拟行为体模型的问题。实现工具性演员模型需要快速,这在命令式编程中是无法实现的。在这种情况下,最佳解决方案是使用角色元编程。现有的许多语言都可以实现这种编程。
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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