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Autore principale: Knar, Eldar
Natura: Preprint
Pubblicazione: 2024
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Accesso online:https://arxiv.org/abs/2501.00043
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author Knar, Eldar
author_facet Knar, Eldar
contents This study proposes an approach to describing personality dynamics through mathematical modelling of introversion, extroversion, and ambiversion processes. Introversion is interpreted as a recursive process characterized by deep self-awareness and inner reflection; extroversion is presented as an iterative process of accumulating and processing external stimuli; and ambiversion is considered transitivity, integrating the interaction of these two opposing processes. The developed model is based on principles of complex systems theory, nonlinear dynamics, and synergetics, enabling the perception of personality as an adaptive and multilayered system. The results include analytical equations describing the interaction of internal and external factors. Parameters regulating personality dynamics, such as sensitivity coefficients, weighting factors of stimuli, and synergy parameters, are also explored. The practical significance of the proposed model lies in its application in psychotherapy, education, personnel management, and other areas where it is necessary to consider personality traits and their dynamics. The model provides new opportunities for diagnosing, forecasting, and correcting personality changes, enhancing methods of working with individuals. The findings open some prospects for quantitative personality analysis, providing a theoretical understanding of its structure and dynamics. They also create a foundation for further interdisciplinary research in psychology, the cognitive sciences, and social systems. Specifically, the formalization considered in the context of program algorithms allows for the creation of functional procedures for AI and robots with differentiated psychological archetypes (introvert robots, extrovert robots, and ambivert robots).
format Preprint
id arxiv_https___arxiv_org_abs_2501_00043
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Recursive introversion, iterative extroversion and transitive ambiversion
Knar, Eldar
Physics and Society
Neurons and Cognition
91
This study proposes an approach to describing personality dynamics through mathematical modelling of introversion, extroversion, and ambiversion processes. Introversion is interpreted as a recursive process characterized by deep self-awareness and inner reflection; extroversion is presented as an iterative process of accumulating and processing external stimuli; and ambiversion is considered transitivity, integrating the interaction of these two opposing processes. The developed model is based on principles of complex systems theory, nonlinear dynamics, and synergetics, enabling the perception of personality as an adaptive and multilayered system. The results include analytical equations describing the interaction of internal and external factors. Parameters regulating personality dynamics, such as sensitivity coefficients, weighting factors of stimuli, and synergy parameters, are also explored. The practical significance of the proposed model lies in its application in psychotherapy, education, personnel management, and other areas where it is necessary to consider personality traits and their dynamics. The model provides new opportunities for diagnosing, forecasting, and correcting personality changes, enhancing methods of working with individuals. The findings open some prospects for quantitative personality analysis, providing a theoretical understanding of its structure and dynamics. They also create a foundation for further interdisciplinary research in psychology, the cognitive sciences, and social systems. Specifically, the formalization considered in the context of program algorithms allows for the creation of functional procedures for AI and robots with differentiated psychological archetypes (introvert robots, extrovert robots, and ambivert robots).
title Recursive introversion, iterative extroversion and transitive ambiversion
topic Physics and Society
Neurons and Cognition
91
url https://arxiv.org/abs/2501.00043