The idea of the theoretical cycle of research is to formalize assumptions, to see if they can be underpinned by derivations from first principles. This method is characteristic of mathematics, in which a theorem usually starts as a conjecture that calls for a proof. The search for a proof may be successful, but may also lead to the conclusion that the conjecture is false or has to be adjusted to be provable. A successful proof means that the correctness of the conjecture can be derived logically from facts proved earlier, and hence, from first principles.

In this first part, Chapter 1 sets the stage by presenting an overview of visual information-processing ideas adhered in structural information theory (SIT). The central idea in SIT is the simplicity principle, which holds that the visual process yields simplest organizations of stimuli. An implicit assumption then is that such organizations have evolutionary survival value in that they are sufficiently veridical to guide us through the world. In Chapter 2, this assumption is addressed in a historical and multidisciplinary setting, using findings from the mathematical domain of algorithmic information theory (AIT). SIT and AIT developed independently of each other, but provide similar modern alternatives for Shannon's (1948) classical selective-information theory.

Notice that Chapter 2 contains mathematical proofs which, however, do not pinpoint the exact degree of veridicality of simplest perceptual organizations (which is probably impossible; see also the Prologue).