Ecological Homeostasis Infrastructure A Forensic Architecture for Reasoning Under Irreversible Uncertainty

AbstractThis paper develops an epistemic and methodological infrastructure for studying, govern-ing, and teaching complex deterministic systems whose predictability collapses beyond nitehorizons. Using the gravitational three-body problem as a limiting case of non-homeostaticdynamicswhere perturbations amplify, equilibria are absent, and prediction failsthe workbuilds a forensic, ensemble-based approach that treats the collapse of causal chaining as anepistemic event rather than a failure. The contribution is not new physics but a reusable in-frastructure pattern: sensing predictability horizons, characterizing ensemble-level structure,and designing adaptive responses that operate on coarse-grained outcomes.Framed within the SHAI (human-aligned interpretation) and HATI2 (honest, accurate,transparent, insightful, impact-oriented) principles, the paper addresses critiques of priorformulations by (1) acknowledging the mixed (regular+chaotic) structure of phase space, (2)specifying the institutional requirements for governance application, (3) replacing detectionwith rigorous estimation under uncertainty, (4) providing a domain-specic implementationsketch with computational scaling and validation protocols, (5) detailing decision-triggermechanisms, and (6) incorporating anti-capture safeguards for governance institutions. Theresult is an infrastructure pattern positioned as a component of ecological homeostasis atcommunity and governance scales, where stability depends not on controlling subsystemsbut on knowing when prediction ends and adaptive response must begin.Keywords: deterministic chaos, three-body problem, Lyapunov exponents, predictabilityhorizon, ensemble methods, coarse-graining, governance under uncertainty, ecological home-ostasis, forensic methodology