Friction-MARL: Factorial Results and Control Battery for the Consent-Friction Functional in Multi-Agent Coordination

Code and complete results for the Friction-MARL study — the empirical companion to The Axiom of Consent (arXiv:2601.06692), testing the consent-friction functional F = σ(1+ε)/(1+α) among Independent Q-Learning (IQL) and Value-Decomposition (VDN) agents in a shared-resource coordination MDP (four agents, three capped continuous resources; reward is the negative weighted squared distance from each agent's ideal state). Version 2.0 adds a control battery to the original 5×5×5 factorial: σ-normalization: the apparent “stakes dominate” effect is mechanical (degree-1 reward scaling); on the stake-normalized gap, preference alignment is the dominant structural factor. Value decomposition (VDN): the coordination patterns are not specific to independent learning. Signed preference DGP: the original factorial's α varied only the magnitude of an always-positive cross-agent correlation; a genuinely signed equicorrelated design (plus two-team and n=2 designs reaching ρ=−1) shows the earlier symmetric “U-shape” was a sign-blind data-generating-process artifact. Separable-resource control: the surviving cooperation effect flattens when agents act on independent pools — the friction is shared-state contention, not preference correlation per se (bounded to common-pool environments). n=2 clean strong-opposition: at genuine unconfounded ρ=−1, opposition does not beat indifference; only cooperative alignment reduces coordination friction. Contents: the friction_marl package (environment, IQL/VDN agents, factorial design), run scripts, and results/ for the full factorial (CPU and GPU), GPU/CPU cross-validation, and the control experiments (review_upgrade, adversarial_rerun including the functional-form refit, reviewer3_controls). Per-experiment FINDINGS.md files and the accompanying paper are authoritative for interpretation. Reproducibility: Python; see requirements.txt / pyproject.toml. Heavy raw artifacts and figure renders that are excluded from the public GitHub repository are included here. License CC-BY-4.0.