  This paper proposes a framework for optimising the adaptation and attunement
of a Complex Adaptive System (CAS) with its environments. The tendency towards
stability can be explained by minimising free energy but high variability,
noise, and over-specialized rigidity can lead to a "stuck state" in a CAS.
Without perturbation (increasing free energy), the system remains stuck and
unable to adapt to changing circumstances. The paper introduces the concept of
'psychotic' Markov blankets to understand and specify factors contributing to
maladjustment conditions moving away from the minimum stuck state. The paper
offers directions for optimising adaptation and attunement to be applied to
real-world problems, from cells to behaviour, societies and ecosystems.
