Attractor Diversity Stabilization in Neuromorphic-Inspired Computational Models (v3.1.0)

When deliberative systems converge prematurely to consensus, minority perspectives vanish - a "tyranny of the majority" encoded in the mathematics of coupled oscillators. We introduce Mem4ristor v3.1.0, a neuromorphic-inspired computational model where constitutional doubt (u) and structural heretics mathematically prevent uniformization. Crucially, we formalize the Repulsive Social Coupling mechanism via a Levitating Sigmoid kernel f(u) = tanh(π(0.5 − u)) + δ and demonstrate that the 15% heretic ratio serves as a critical threshold for cognitive diversity emergence starting from zero entropy (Cold Start Protocol, requiring noise). Version 3.1.0 introduces two adaptive extensions: (1) Adaptive Meta-Doubt, where the doubt learning rate εu accelerates proportionally to social surprise σsocial, providingsocial-surprise-driven meta-plasticity; and (2) Doubt-Driven Topological Rewiring, where high-doubt units disconnect from consensual neighbors and reconnect to random non-neighbors, resolving hub strangulation in scale-free networks. Grounded in phenomenological mapping to memristive systems, our model demonstrates Attractor Diversity Stabilization (H ≈ 1.56 bits, Shannon entropy over 5 cognitive states). Stress-testing reveals a "Fragility Law": the absence of structural heretics triggers a significant collapse in global cognitive diversity. This work represents a computational exploration of Frustrated Synchronization, where doubt servesas the necessary frustration to maintain simulated system-level intelligence.