Free-energy minimization and the dark-room problem

Recent years have seen the emergence of an important new fundamental theory of brain function. This theory brings information-theoretic, Bayesian, neuroscientific, and machine learning approaches into a single framework whose overarching principle is the minimization of surprise (or, equivalently, the maximization of expectation). The most comprehensive such treatment is the 'free energy minimization' formulation due to Karl Friston (see e.g. Friston and Stephan (2007), Friston (2010) see also Thornton (2010), Fiorillo (2010) A recurrent puzzle raised by critics of these models is that biological systems do not seem to avoid surprises. We do not simply seek a dark, unchanging chamber and stay there. This is the 'Dark Room Problem'. Here, we describe the problem and further unpack the issues to which it speaks. Using the same format as the prologue of Eddington's Space, Time and Gravitation (Eddington 1920) we present our discussion as a conversation between