THE ASYMMETRY PROTOCOL: Sustaining Recursive Stability through Functional Dissonance in AI Agents

Previous work established that recursive AI agents reach terminal semantic collapse when isolated from external grounding. This paper investigates the stabilization of such systems through the implementation of the Asymmetry Protocol. We compare three distinct grounding regimes: passive stochastic anchoring, semantic noise injection, and active cognitive dissonance via the Paradox Engine. Our results demonstrate that while passive anchors lead to ritualistic repetition, the introduction of irresolvable logical contradictions forces agents to maintain semantic novelty. We conclude that sustained intelligence is a dynamic process of resistance against informational symmetry, requiring irresolvable cognitive tension as a necessary design parameter for stable AGI architectures.