Human-Centric Functional Modeling and the Convergence of Science

This paper explores Human-Centric Functional Modeling as a universal modeling methodology with the potential to be used for representing all systems both conceptually and functionally, and it explores what capacity for convergence in our understanding of systems means in terms of Human-Centric Functional Modeling, how that capacity might be quantified, and why Human-Centric Functional Modeling as a methodology might maximize our collective capacity to achieve convergence in our understanding across all sciences and across the systems that those sciences study.

Human-Centric Functional Modeling and Metatheories of Psychology

The newly emerging science of Human-Centric Functional Modeling provides an approach towards modeling systems that is hypothesized to maximize human capacity to understand and navigate complexity in those systems. This paper provides an overview exploring how Human-Centric Functional Modeling might be applied in psychology, and how this increase in capacity to understand complexity might be achieved within the discipline. One potential application is increasing our capacity to compare metatheories of psychology. Given that developing and/or understanding any one particular metatheory of psychology can be a life-long achievement, and assuming that understanding and comparing more than one or two such metatheories might be outside the cognitive capacity of most individuals, one potential key area of usefulness for Human-Centric Functional Modeling is that it provides a single universal way of modeling the human organism and its psychology so that all such metatheories might be compared in each context of their use in order to collectively converge on a single meta-understanding of psychology and of clinical interventions in psychology that best reflect observations.

Human-Centric Functional Modeling and Evolutionary Biology

The newly emerging science of Human-Centric Functional Modeling provides an approach towards modeling biological and other systems that is hypothesized to maximize human capacity to understand and navigate complexity in those systems. This paper provide an overview exploring how Human-Centric Functional Modeling might be applied in evolutionary biology, and how this increase in capacity to understand the complexity that organisms have evolved into might be achieved. The broader usefulness of Human-Centric Functional Modeling is that it provides a simple mathematical definition of what constitutes a biological system, defines the problem-solving domain of any biological system in terms of abstract mathematical spaces, and provides an expression defining general problem-solving ability in any such domain. This enables it to be seen that all systems with general problem-solving ability in their own domain are potentially an abstraction of a single mathematical pattern of adaptive problem-solving that might apply to all domains. From this perspective nature has already potentially solved problems in biological organisms that can be represented in some abstract functional state spaces as the same general problem that must be solved to address problems in a wide range of other systems, including existential challenges from poverty to climate change, where Human-Centric Functional Modeling enables it to be seen that not only can nature’s solutions be copied, but that nature has demonstrated its solutions to have worked for hundreds of millions of years.

Human-Centric Functional Modeling and Condensed Matter Physics

The newly emerging sciences of Human-Centric Functional Modeling provides an approach towards modeling systems that is hypothesized to maximize human capacity to understand and navigate complexity in those systems. This paper provide an overview exploring how Human-Centric Functional Modeling might be applied in condensed matter physics, and how this increase in capacity to understand complexity might be achieved.

Functional State Spaces and their Formation in Systems from Biological Organisms to the Physical Universe

This paper explores how the emerging science of Human-Centric Functional Modeling or HCFM provides a universal approach to modeling systems that is hypothesized to maximize human capacity to understand and navigate the complexity of systems, and how it facilitates a kind of biomimicry in which the human organism is represented in terms of abstract mathematical spaces that can be used to define simple expressions to represent properties like “complexity” for human systems like cognition, where the same spaces can be used to represent other systems, including the entire physical universe, so that the underlying equivalence of the representations allows the same mathematical expressions to define the same properties where applicable for these very different systems, and therefore allows deep insights to potentially be gained about these systems through looking inward to observe how one’s own cognition functions from one’s first person experience. This paper explores how from this Human-Centric Functional Modeling perspective the properties governing the evolution of life in its functional state space might also govern the formation of the universe in its own functional state space. Human-Centric Functional Modeling also has other significant benefits, one is that in defining behavior in terms of mathematical spaces it enables all the mathematical disciplines that apply to such spaces (e.g. functor theory, category theory, process theory) to be used to understand and navigate the relationships between concepts described in those spaces. Another is that in providing a self-contained representation of the human meaning of any entity, including of any region in the physical universe, Human-Centric Functional Modeling potentially defines the first complete semantic representation of concepts, physical objects, or any other entities represented in a functional state space. When applied to the physical universe this implies that all theoretical or experimental data can be stored in that single model and all theories tested against it to increase capacity to impact a research question. When applied to other systems semantic modeling has equally important implications. Another benefit of Human-Centric Functional Modeling is that it is also a human-centric expression of “constructor theory”, which in the case of physical systems enables accurate predictions to be made about their physical behavior simply from observations of their functions, without needing to understand the specific physics through which the functions are implemented in those systems.

System Modeling of Author’s Image in Texts of One Speech Genre

The question of the method of describing of Author’s Image in Texts in modern linguistics is discussed in the article. It is argued that this technique requires the development of principles focused on systems engineering. The authors of the article note that one of the problems of modern genre studies is that a large amount of research in this area in aggregate reflects various approaches to the description of the “image of the author” in texts of the genre. The novelty of the research is seen in the fact that for an objective description of the author’s image, the hypothesis of “Functional modeling of the author of the genre” is put forward: the model of the genre system in the epistemological description has a complex level structure. The authors of the article put forward their own development of the technology for describing the image of the author of the genre, defining this technology as effective and consistent with the principles of a systematic approach to genre phenomena. In order to solve the problem of the attributive aspect of describing a genre, that is, to determine its units, it seems productive to analyze the genre according to the so-called communicative-semiotic model. The article proposes ways of solving emerging problems concerning the principles of objectivist description of the author’s model of the genre.