AI RESEARCH
Constitutional Governance in Metric Spaces
arXiv CS.AI
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ArXi:2605.13362v1 Announce Type: cross Computational social choice and algorithmic decision theory offer rich aggregation theory but no end-to-end, polynomial-time process for egalitarian self-governance: prior work treats aggregation, deliberation, amendment, and consensus in isolation, and key metric-space aggregators are NP-hard. We propose constitutional governance in metric spaces, integrating these stages into one polynomial-time process. The constitution assigns, per amendable component, a metric space, aggregation rule, and supermajority threshold.