On the computational rationale for generative models

Generative and discriminative models are best defined by the structure of their graphical representation. This paper introduces such a definition and uses it to argue that, in some practical cases, generative models need to be formulated in order to be implemented within generate-and-test algorithms. This argument is inspired mainly by the ideas of the late Donald MacKay and by considerations of computational complexity.