 The idea that algorithmic complexity theory is a foundation for a general theory of artificial intelligence (and theory of knowledge) has already been suggested by Solomonoff (1997) and Chaitin (1987). Several authors have defended that data compression is a general principle that governs human cognition (Chater &amp; Vitányi 2003; Wolff 2006). Hutter (2005, 2007a,b) argues that Solomonoff’s formal and complete theory essentially solves the induction problem. Hutter (2007a) and Rathmanner &amp; Hutter (2011) enumerate a plethora of classical philosophical and statistical problems around induction and claim that Solomonoff’s theory solves or avoids all these problems. Probably because of its technical nature, the theory has been largely ignored by the philosophical community. Yet, it stands out as one of the most fundamental contributions to information theory in the twentieth century and it is clearly relevant for a number of philosophical issues, such as the problem of induction.