  In the monograph, STRONG ARTIFICIAL INTELLIGENCE. On the Approaches to
Superintelligence, published by Sberbank, provides a cross-disciplinary review
of general artificial intelligence. As an anthropomorphic direction of
research, it considers Brain Principles Programming, BPP) the formalization of
universal mechanisms (principles) of the brain's work with information, which
are implemented at all levels of the organization of nervous tissue. This
monograph provides a formalization of these principles in terms of the category
theory. However, this formalization is not enough to develop algorithms for
working with information. In this paper, for the description and modeling of
Brain Principles Programming, it is proposed to apply mathematical models and
algorithms developed by us earlier that model cognitive functions, which are
based on well-known physiological, psychological and other natural science
theories. The paper uses mathematical models and algorithms of the following
theories: P.K.Anokhin's Theory of Functional Brain Systems, Eleonor Rosh's
prototypical categorization theory, Bob Rehter's theory of causal models and
natural classification. As a result, the formalization of the BPP is obtained
and computer examples are given that demonstrate the algorithm's operation.
