论文标题
大脑编程原理的形式化（大脑原理编程）
Formalization of the principles of brain Programming (Brain Principles Programming)
论文作者
论文摘要
在专着“强大的人工智能。关于超级智能的方法”中包含通用人工智能（AGI）的概述。作为一个拟人化研究领域，它包括大脑原理编程（BPP） - 大脑的普遍机制（原理）的形式化，并在神经组织组织的各个层面上实施。该专着在类别理论方面包含了这些原则的形式化。但是，这种形式化不足以开发用于使用信息的算法。在本文中，对于BPP的描述和建模，建议采用较早开发的数学模型和算法，该模型和算法对认知功能进行了建模，并基于众所周知的生理，心理和其他自然科学理论。本文使用以下理论的数学模型和算法：P.K.Anokhin功能性脑系统理论，Eleanor Rosch原型分类理论，Bob Rehder因果模型和“自然”分类。结果，获得了BPP的形式化，并提供了证明算法运行的计算机实验。
In the monograph "Strong artificial intelligence. On the Approaches to Superintelligence" contains an overview of general artificial intelligence (AGI). As an anthropomorphic research area, it includes Brain Principles Programming (BPP) -- the formalization of universal mechanisms (principles) of the brain work with information, which are implemented at all levels of the organization of nervous tissue. This monograph contains a formalization of these principles in terms of category theory. However, this formalization is not enough to develop algorithms for working with information. In this paper, for the description and modeling of BPP, it is proposed to apply mathematical models and algorithms developed earlier, which modeling cognitive functions and base on well-known physiological, psychological and other natural science theories. The paper uses mathematical models and algorithms of the following theories: P.K.Anokhin Theory of Functional Brain Systems, Eleanor Rosch prototypical categorization theory, Bob Rehder theory of causal models and "natural" classification. As a result, a formalization of BPP is obtained and computer experiments demonstrating the operation of algorithms are presented.
