When Correct Actions Are Not Enough: Regime Admissibility in Long-Horizon Adaptive Systems

This work examines the problem of long-horizon viability and preservation of organizational identity in adaptive systems operating under uncertainty, partial observability, and prolonged interaction with their environment. It shows that typical control and learning architectures—from classical control and reinforcement learning to safety controllers, shields, and reward shaping—act primarily through causal intervention in action selection, optimization, and policy updates, and therefore remain “blind” to slow structural degradation unfolding over extended time scales. The author introduces a distinction between action-centric regulation and long-horizon properties of viability and identity, understood as global, cumulative characteristics of system organization rather than properties of individual actions or short trajectories. The text argues that when evaluation of such properties is embedded into the same channels that generate behavior (rewards, penalties, constraints, gradients), causal entanglement arises: the system begins to optimize not the underlying structure, but the indicators themselves, leading to behavioral distortion, feedback amplification, and masking of slow degradation. The main contribution of the work is conceptual and architectural. It formulates the need for a separate, non-causal dimension of observation for long-horizon viability and identity continuity that coexists with behavioral mechanisms but does not become another optimization target. No specific algorithms, controllers, or implementation schemes are proposed; instead, the text delineates the problem space and establishes prior art for future architectures in which long-term viability is treated as an independent dimension of observation and interpretation rather than as a side effect of locally correct actions.