This paper derives a necessary dual-layer architecture for adaptive cognitive systems operating under non-ideal conditions. By separating a hard, immutable layer from a dynamic, adjustable one, the framework resolves the structural trade-off between stability and adaptive capacity. The model applies both to persistent artificial systems and to human cognition under uncertainty and irreversibility.
David Grossi Fernandez (Sat,) studied this question.