Computational Machines in a Coexistence with Concrete Universals and Data Streams

TL;DR

This paper proposes a new conceptual modeling framework called pre-specific modeling, based on concrete universals and category theory, addressing limitations of traditional set-theoretical models in complex systems with diverse perspectives.

Contribution

It introduces pre-specific modeling as an alternative to idealist set-theoretical models, utilizing category theory and data streams to operationalize complex system representations.

Findings

Pre-specific modeling offers a flexible approach for complex systems.

Mathematical and computational methods can operationalize pre-specific modeling.

The framework addresses limitations of traditional models in multi-perspective complex systems.

Abstract

We discuss that how the majority of traditional modeling approaches are following the idealism point of view in scientific modeling, which follow the set theoretical notions of models based on abstract universals. We show that while successful in many classical modeling domains, there are fundamental limits to the application of set theoretical models in dealing with complex systems with many potential aspects or properties depending on the perspectives. As an alternative to abstract universals, we propose a conceptual modeling framework based on concrete universals that can be interpreted as a category theoretical approach to modeling. We call this modeling framework pre-specific modeling. We further, discuss how a certain group of mathematical and computational methods, along with ever-growing data streams are able to operationalize the concept of pre-specific modeling.