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.