On the Complexity of Causal Models

It is argued that a principle of casuality is fundamental to human thinking, and it has been observed experimentally that this assumption leads to complex hypothesis formation by human subjects attempting to solve comparatively simple problems involving acausal randomly generated events. This correspondence provides an automatatheoretic explanation of this phenomenon by analyzing the performance of an optimal modeler observing the behavior of a system and forming a minimal-state model of it.