Solving the problem of problem-solving and of seeking best-solutions to difficult, complex or “wicked” problems is no trivial task. Acknowledging from the outset that there is no one-size-fits-all solution generates both complexity and simplicity in analysis. Complexity emerges because the scope and range of analysis required for any particular problem-set may be completely unique, undefined or undefinable. Simplicity also emerges but for the reason that it is possible to reduce sets of problems to grouped taxonomies and hierarchies of category based upon perceived or attributed statistical or structural similarity, cycle or regularity.
The topography and landscape of complex problem-solving possesses something of the characteristics of an amusement park for the intellect. Groups, classes or sets of similar problems as definable by similar forms of experience, analysis or empirical data are located in particular conceptual places and tend to cluster around each other in regards to methods and frameworks of analysis.
Working under a holistic, meta-theoretical framework of “what is the central similarity or notionally gravitational and logical pivot ?” of explanatory systems introduces multiple considerations of #epistemology (Knowledge) and #ontology (Existence/Being). I am not seeking closure or truth so much as direction and possibility.