Dynamic Rule Spectrum System (DDRS): A Ten-Layer Pressure Field Architecture for Modeling Rule Activation, Attractor Coupling, and Path Selection in Large Language Models

The Dynamic Rule Spectrum System (DDRS) extends the Generative Behavior Science Framework (GBSF) seven-layer static model into a ten-layer dynamic rule pressure field architecture capable of representing rule activation dynamics, inter-layer coupling, attractor emergence, and path selection under multi-rule competition. DDRS introduces three constructs: the Rule Pressure Field (RPF), Attractor-Rule Coupling Coefficient (ARCC), and Path Entropy Signature (PES). Fifteen experimental conditions (EXP-046-A through -O) document rule stack crystallization, attractor-induced rule suppression, and rule-layer boundary dissolution. All results are hypothesis-generating observations (V1–V2 claim ceiling) requiring multi-experimenter replication. This record is part of the Sangzi Wang Generative Behavior Science / Model Behavior Observatory research series.