Replication processes in Specific Artificial Intelligence for Artificial Research by Deduction

This paper investigates the role of replication processes in the context of Specific Artificial Intelligence (SAI) designed for Artificial Research by Deduction. Unlike general replication in machine learning or biological metaphors in AI, replication in deductive SAI refers to the structured reproduction of reasoning procedures, axiomatic configurations, and proof systems across similar or extended research environments. These processes ensure that deductive capabilities can be transferred, reused, and systematically scaled while preserving logical consistency and epistemic integrity. The paper proposes a modular replication architecture that allows for the replication of logical inference mechanisms and the controlled distribution of formal knowledge bases across instances of SAI. This approach facilitates the testing, validation, and progressive expansion of deductive research capabilities in a reliable, traceable manner. Furthermore, replication in SAI is presented as a critical preparatory step toward enabling such functionalities at the scale of Global Artificial Intelligence (GAI), allowing deductive systems to evolve and refine themselves through consistent and provable mechanisms.