Theoretical framework reveals a tick-based architecture for inspectable inner states in language models, indicating potential paths toward persistent, causally grounded machine interaction.
Standard language-model inference lacks cross-exchange internal organization. External memory can reconstruct continuity without persistent state whose causal role is tested. We present TASA (Tick-Based Affective State Architecture), a theoretical framework for such a state: segmented across timescales in discrete ticks, with structured affect, competitive workspace integration, governed typed memory shelves, and language isolated behind translators. TASA contributes (i) a semi-formal architecture specification; (ii) five conditions for latent-target learning and assessment—four target/optimization conditions plus one persistence-discriminability reporting condition—with failure modes including identity solutions and conditional-mean collapse; (iii) growth governance based on memory-first consolidation, no-self-sealing, and criterion reachability; and (iv) an evaluation theory with noise floors, structurally equivalent positive controls, item-level statistics, evidence markers, and staged understanding. A worked instantiation sketches an inspectable end-to-end interaction loop whose prototype core is memory- and complexity-plausible on one GPU; throughput and repeat-run affordability remain unmeasured. Seventeen hypotheses—fourteen non-provisional and three provisional—define the program. The non-provisional hypotheses become bidirectionally testable once a study versions its estimands, controls, and decision rules. This framework paper reports no empirical results; its contribution lies in methodological integration and operationalization. The long-horizon aim is to test whether persistent state becomes measurably richer, more coherent, more history-dependent, and deeper during sustained, governed operation. All such claims require instrumentation, and terms such as affect and inner state denote functional organization rather than consciousness, sentience, or phenomenal experience.
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Sebastian Fuchs (2026) studied this question.
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