History-Conditioned Control in Open Systems

This corrected preprint presents its research question, method, bounded result, and principal limitations in a standardized reader-facing format. Purpose-like descriptions are common in biology, neuroscience, robotics, and artificial intelligence, but the same language is often applied to systems with radically different capacities. A falling object follows a gradient, a thermostat corrects a measured error, a cell changes its behavior after stress, and a planning agent compares alternatives. Dissipation and stabilization alone do not make these systems equivalent. This paper develops a bounded mathematical framework for distinguishing four evidential levels: physical dissipation, regulation, history-conditioned adaptive control, and conditional agency. The core proposal is that a system becomes usefully teleonomic when internally accessible history changes its response to otherwise matched present conditions, returned consequences update that history, and the resulting policy differences survive matched null models and causal interventions. It belongs to Micah Blumberg's governed research-paper corpus. This is a corrected preprint edition released under the Creative Commons Attribution 4.0 license.