The Role of MetaPhysics in Factasia


Metaphysics is positioned in Factasia as starting from an abstract basis provided by logic and mathematics building on this the concepual frameworks necessary for articulating scientific theories as logical or mathematical models of aspects of reality.
The Analytic/Synthetic Dichotomy
We cling to the "empiricist dogma" of the Analytic/Synthetic dichotomy, but nevertheless find a place for metaphysics, providing analytic prolegomena to science.
Logic and Abstraction
Abstract ontology, because of its intimate connection with matters of logical consistency, is considered a part of logic. Ontology is considered arbitrary within the bounds of consistency, is determined on a pragmatic basis, and need not be unique. We advocate logical foundations within which mathematical models adequate for science and engineering can be developed by conservative extension.
Once a logical foundation has been provided, mathematics can be developed in a manner similar to that first shown in Principia Mathematica. Gödel's incompleteness results have minimal practical impact upon this.
Once equipped with a well-founded logical and mathematical framework, MetaPhysics can address the preliminary aspects of building mathematical models of the real world, e.g. the structure of space-time and concrete ontology.
Science and Engineering
Within the conceptual framework provided by metaphysics, science formulates and evaluates mathematical models of real world phenomena. Formally these models are developed within the established foundational framework, using only conservative extensions. As such the definition of these model is analytic. These models form the basis for engineering design, which solves engineering problems in this abstract domain before building the solutions in the real world.
The Analytic Superbrain This story is not about the role of metaphysics in today's science and engineering, but part of a design for a future analytic superbrain which automates large parts of engineering design using formal scientific models.


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