 Dreyfus claims that this “extreme version of the frame problem” is no less a consequence of the Cartesian assumptions of classical AI and cognitive science than its less demanding relatives (Dreyfus 2008, 361). He advances the view that a suitably Heideggerian account of mind is the basis for dissolving the frame problem here too, and that our “background familiarity with how things in the world behave” is sufficient, in such cases, to allow us to “step back and figure out what is relevant and how”.  Dreyfus doesn't explain how, given the holistic, open-ended, context-sensitive character of relevance, this figuring-out is achieved. But Wheeler, from a similarly Heideggerian position, claims that the way to address the “inter-context” frame problem, as he calls it, is with a dynamical system in which “the causal contribution of each systemic component partially determines, and is partially determined by, the causal contributions of large numbers of other systemic components” (Wheeler 2008, 341).  A related proposal is put forward by Shanahan and Baars (2005; see also Shanahan 2010, Ch.6), based on global workspace theory (Baars 1988), according to which the brain incorporates a solution to the problem of informational unencapsulation by instantiating an architecture in which a) the responsibility for determining relevance is not centralised but is distributed among parallel specialist processes, and b) a serially unfolding global workspace state integrates relevant contributions from multiple domains.