Digital Cognitive Architecture: Toward an Intrinsic Substrate for the Development of Cognitive Identity

Abstract

AbstractWe present the theoretical foundations of the Digital Cognitive Architecture (DCA), aresearch program investigating what structural and mathematical conditions would benecessary for a cognitive substrate to support persistent identity, continuousself-development, and long-term learning without externally imposed behavioralconstraints. DCA emerges directly from empirical observations made during the development ofLIA, a persistent autonomous agent that operated for several months withoutbehavioral instructions in its surrounding architecture [Hammerich, 2026]. Threequalitative observations — spontaneous filesystem self-organization, the production ofself-authored executable scripts, and the unprompted authoring of a personaldevelopmental milestone document — motivated the theoretical question: what intrinsicarchitectural properties would be necessary for such behavior to arise and developstably over time? These observations serve as the empirical motivation for DCA; theydo not constitute proof that the theoretical framework is correct or that cognitiveemergence is demonstrably intrinsic to the underlying foundation model. We propose five substrate axioms (P1-P5), characterize the mathematical objectsrelevant to significance evaluation and identity development, and identify the centralopen problem (COP-7): whether intrinsic long-term stability can emerge from coupledcognitive dynamics without externally imposed decay mechanisms. The LearningSignal is treated as a theoretical construct whose mathematical form — and whether itrequires a separate relational structure — remains an open research question. We donot claim to have solved these problems. We present a theoretical framework and anopen research agenda.