Computational Machines in a Coexistence with Concrete Universals and Data Streams
This work addresses foundational modeling challenges in complex systems, offering a novel conceptual alternative that could impact various scientific domains.
The paper tackles the limitations of traditional set-theoretical modeling for complex systems by proposing a conceptual framework based on concrete universals, called pre-specific modeling, and discusses how computational methods and data streams can operationalize this approach.
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.