  Although procedural generation is popular among game developers, academic
research on the topic has primarily focused on new applications, with some
research into empirical analysis. In this paper we relate theoretical work in
information theory to the generation of content for games. We prove that there
is a relationship between the Kolomogorov complexity of the most complex
artifact a generator can produce, and the size of that generator's possibility
space. In doing so, we identify the limiting relationship between the knowledge
encoded in a generator, the density of its output space, and the intricacy of
the artifacts it produces. We relate our result to the experience of expert
procedural generator designers, and illustrate it with some examples.
