Meta-Abstract Architectural Limits of Long-Horizon Adaptive Systems

This work addresses a fundamental limitation in existing adaptive system architectures: the inability to observe long-horizon viability and identity continuity without making such observation causally operative with respect to behavior, learning, or optimization. In real-world operation, adaptive systems frequently fail not due to incorrect actions or local performance errors, but due to gradual structural degradation and erosion of organizational identity. Such degradation often remains invisible to action-level metrics, rewards, or constraints, leading to sudden failure or loss of adaptability despite apparent short-term correctness. The work identifies the architectural consequences of causally entangling observation with control. When viability- or identity-related evaluation is embedded into decision-making loops, monitoring signals inevitably become optimization targets, inducing feedback amplification, metric gaming, or silent degradation masked by preserved performance indicators. This paper establishes prior art for the conceptual distinction between action-centric regulation and non-causal observation of long-horizon structural properties. It formalizes the problem space in which viability and identity must be treated as global, temporally extended properties that cannot be reliably assessed from within an agent’s decision surface without distorting behavior. No specific mechanisms, algorithms, or architectures are disclosed. Instead, the contribution is architectural and conceptual: to delineate the necessity of a non-causal observational dimension for long-horizon adaptive systems. Any system that introduces an observational layer capable of evaluating viability or identity continuity without influencing action selection, learning, or optimization operates within the conceptual space defined by this work. This research is part of the broader Project Petronus, which investigates architectural foundations for long-horizon autonomy, viability preservation, regime dynamics, and identity continuity in adaptive and autonomous systems.