Human-Centric Functional Modeling and the Unification of Systems Thinking Approaches

Abstract

Where systems thinking approachesare often different and sometimes irreconcilable because they are based on the reasoning of one individual or another, Human-Centric Functional Modeling aims to become universal through looking inwards to the way all human beings perceive. HCFM provide a methodology that enables first person observations within each of the senses of the body or within the emotions, mind, or consciousness as functional systems to be represented as forming mathematical spaces that in turn enable all possible systems thinking approaches to be represented.This creates the possibility of comparing all systems thinking approaches to determine which is most “fit” in each context in which it is used, and it radically reduces the barriers to reusing the best components of each approach.

Automating the Process of Generalization

“…Various scholars have hypothesized that the behavior of any system can be represented in terms of network graphs called state spaces [1], [2], [3]. The emerging science of Human-Centric Functional Modeling or HCFM [4] elaborates the concept of state spaces into "functional state spaces" that each represent a separate domain of behavior for each system. Each state within these spaces is considered a "functional state" because the system transitions into or out of that state through one or more potentially observable processes.…”

Using General Collective Intelligence to Optimize the Process of Evolutionary Optimization

“…Human-Centric Functional Modeling or HCFM [6] postulates that the behavior of potentially all systems can be represented in terms of functional state spaces. In the case of intelligent systems such as AI, HCFM postulates that all such computing programs are an automation of human pattern recognition processes (type 1 reasoning) and/or an automation of human logical processes (type 2 reasoning).…”

Elevating Science to Detect Unsolvable Problems

“…Human cognition can also solve computable problems through type 2 reasoning where a chain of reasoning (that is, an algorithm) exists, where the information required to evaluate that algorithm exists, and where the capacity to evaluate that algorithm exists. The newly emerging science of Human-Centric Functional Modeling [2] represents thought (concepts and reasoning) in terms of a space of concepts or "conceptual space" which the cognitive system moves through in the process of executing the reasoning with which it navigates from one concept to the next. In this conceptual space, complexity of type 1 or type 2 reasoning is defined by the distance navigated through conceptual space, multiplied by the density of concepts the reasoning must navigate through.…”