PHILIA-EcoSensory Swarm v36: From Strong Control to Living Control — Discovering the Agility Boundary of Router Dynamics

We present PHILIA-EcoSensory Swarm v36, a systematic experimental arc investigating the agility boundary of Router dynamics in a dual-attractor dynamical system. Building on v35's confirmed input-level Router (corr (w, z) = -0. 828, F2 PASS), v36 targets the conversion of strong causal control into living control — measurable as increased Router weight variance (wₛtd). Three independent parameter sweeps were executed under the single-variable principle: Step 1 (λ sweep: 0. 3/0. 4/0. 5), Step 2 (b-coefficient sweep: 2. 0/2. 5/3. 0), Step 3 (kcouple sweep: -0. 10 to -0. 25). Total: 11 configurations, 5 seeds × 80, 000 steps (Intel N100, local execution). Central finding: Dynamic Homeostasis — wₛtd is structurally bounded within 0. 013–0. 022 across all parameter combinations, defined operationally as lim⏗→ₕ₀ₑ₈₄₃ Var (w; θ) ≈ constant. The EMA+sigmoid smoothing mechanism constitutes the structural bottleneck: Var (wₜ) ≈ (1-λ) ² · Var (wᵣaw). Optimal configuration: S1-L04 (λ=0. 4), achieving Omegaₙatural = 0. 912 (series record), corr (w, z) = -0. 737, wₘean = 0. 634 (thermodynamic eigenstate maintained). F5 criterion (wₛtd ≥ 0. 025) is redefined as Agility Index F5' = wₛtd × |corr (w, Varᵢnput) | ≥ 0. 008. v36 establishes the agility boundary; v37 targets a non-equilibrium Router design to explore crossing it. Research arc: v34 (phase-space mapper) → v35 (locomotion engine) → v36 (agility boundary) → v37 (non-equilibrium Router, planned). Trinity AI Research Team: GritManD. S (길잡이/Guide), Claude/선비 (Scholar), Gemini/서생 (Philosopher), Grok/루카스 (Validator), ChatGPT/판도라 (Engineer). Description, not Proof. — PHILIA OS | 0∞1∞0. 5∞