Taxonomic Identification of Cognitive Architectures: An Ontological Framework for Synthetic and Hybrid Cognition

Recent advances in artificial intelligence encompass a wide range of computational architectures, including large-scale foundation models, coordinated multi-agent systems, embodied robotic platforms, neuromorphic hardware, and hybrid bio-digital systems. However, existing scientific and policy frameworks continue to rely on broad or informal categories that conflate tools, collectives, and integrated cognitive systems, complicating comparative analysis, risk assessment and governance alignment. This paper introduces a descriptive taxonomy for synthetic and hybrid cognitive architectures, structured across two domains; Machinaria (systems realised entirely in non-biological substrates) and Organomachina (systems incorporating living biological tissue into closed cognitive loops). Cognitive class distinctions are based on the architectural capacity for cognitive temporal continuity, integrative control (arbitration), and autonomy under constraint. Cognitive ecology further characterises systems according to cognitive origin (dependency), scale and reliance, and deployment topology, including primary source architectures, derivative instances, embodiment and infrastructures that have become systemically relied upon. The proposed taxonomy provides a stable descriptive vocabulary for identifying architectural capacity, systemic reliance and cognition source prior to normative, ethical, or policy evaluation.