{
  "annotation_id": "13954264-88ce-45f7-af4e-d8a884c590ad",
  "date_created": "2026-02-17T05:53:08.614000Z",
  "date_modified": "2026-02-17T05:53:08.614000Z",
  "file_hash": "1098c3c9148e0c718ccbcc97f3c744d967105881ee73796fb4c02d6eb5b0f519",
  "private": false,
  "record": {
    "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.\n  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.\n  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.",
    "arxiv_id": "2601.06692",
    "authors": [
      "Murad Farzulla"
    ],
    "categories": [
      "cs.MA",
      "cs.CY"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "title": "The Axiom of Consent: Friction Dynamics in Multi-Agent Coordination",
    "url": "https://arxiv.org/abs/2601.06692",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "5ad9d0b6-6185-4137-92b7-8f594b177747",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}