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

• URL: http://arxiv.org/abs/2601.06692v1
• Date: Sat, 10 Jan 2026 21:28:41 GMT
• Title: The Axiom of Consent: Friction Dynamics in Multi-Agent Coordination
• Authors: Murad Farzulla,
• Abstract summary: This paper derives a formal framework for analyzing coordination friction from a single axiom.<n>From this axiom of consent, we establish the kernel triple $(,, )$ characterizing any resource allocation configuration.<n> Applications to cryptocurrency governance and political systems demonstrate that the same equations govern friction dynamics across domains.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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 $(α, σ, ε)$ (alignment, stake, and entropy) characterizing any resource allocation configuration. The friction equation $F = σ (1 + ε)/(1 + α)$ predicts coordination difficulty as a function of preference alignment $α$, stake magnitude $σ$, and communication entropy $ε$. 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.

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