The Axiom of Consent: Friction Dynamics in Multi-Agent Coordination

Multi-agent systems face a fundamental coordination problem: agents must coordinate despite heterogeneous preferences, asymmetric stakes, and imperfect information. When coordination fails, friction emerges: measurable resistance manifesting as deadlock, thrashing, communication overhead, or outright conflict. This paper derives a formal framework for analyzing coordination friction from a single axiom: actions affecting agents require authorization from those agents in proportion to stakes. From this axiom of consent, we establish the kernel triple $({\alpha}, {\sigma}, {\epsilon})$ (alignment, stake, and entropy) characterizing any resource allocation configuration. The friction equation $F = {\sigma} (1 + {\epsilon})/(1 + {\alpha})$ predicts coordination difficulty as a function of preference alignment ${\alpha}$, stake magnitude ${\sigma}$, and communication entropy ${\epsilon}$. The Replicator-Optimization Mechanism (ROM) governs evolutionary selection over coordination strategies: configurations generating less friction persist longer, establishing consent-respecting arrangements as dynamical attractors rather than normative ideals. We develop formal definitions for resource consent, coordination legitimacy, and friction-aware allocation in multi-agent systems. The framework yields testable predictions: MARL systems with higher reward alignment exhibit faster convergence; distributed allocations accounting for stake asymmetry generate lower coordination failure; AI systems with interpretability deficits produce friction proportional to the human-AI alignment gap. Applications to cryptocurrency governance and political systems demonstrate that the same equations govern friction dynamics across domains, providing a complexity science perspective on coordination under preference heterogeneity.