Zarncke, 2026 — Recoverability of Smoothed Agent Boundaries in Unsupervised Agent Discovery
Internal source: recoverability theory for UAD under a smoothing/coarse-graining observation channel. Focus: temporal and variable smoothing only recover a boundary up to its channel-induced equivalence class; variable smoothing that mixes agents through a shared aggregate can require testing a coarse-grained candidate, not a better pairwise statistic.
Internal source: recoverability theory for UAD under a smoothing/coarse-graining observation channel. Focus: temporal and variable smoothing only recover a boundary up to its channel-induced equivalence class; variable smoothing that mixes agents through a shared aggregate can require testing a coarse-grained candidate, not a better pairwise statistic.