The Receiver Architecture as a Design Pattern for Adaptive AI Systems: Cross-Substrate Generalization of RPCS-1 (Series-Completing Paper)

Conjecture (Cross-Substrate Generalization) + Failure Mode Predictions + 3 Falsifiable Predictions. The receiver architecture is substrate-independent: adaptive systems regardless of biological or computational substrate share architectural primitives. Mappings: TI to attention window length, SG to gain control and layer normalization, FT to softmax temperature and top-k filtering, UE to learning rate and plasticity scheduling, AR to exploration-exploitation bias. Failure Mode Predictions: oscillation regime (high TI/SG, low FT), overload regime (high SG, low FT, low TI), freeze regime (low UE, high FT). Three Predictions about ML failure modes, multi-agent diversity coverage, human-AI hybrid systems. Alignment-relevant implications stated under the Conjecture. Four structural limitations: substrate independence is Conjecture not Theorem; mapping specificity; coupling unspecified for hybrid systems; adaptation dynamics not modeled. The series-completing paper of the IMM 12-paper decomposition, making explicit the cross-domain claim that projection-driven dynamics organize adaptive systems regardless of scale or substrate. Inherits from Papers 9 and 11.