If I am now asked to construct an information retrieval system or, if you wish, a „brain“ capable of similar, or even more complicated stunts, I would rather think in terms of a small and compact computing device instead of considering tabulation methods which tend to get out of hand quickly.
It has lately become increasingly clear that evolution, in which an ever so slight advantage is immediately associated with a considerable pay-off in survival value, has gone exactly the way I just suggested, trading cumbersome accumulation of isolated operational entities for structural sophistication. Homeostasis is a typical case in question. However, since our topic in this conference is information storage and retrieval, let me give you a very brief account on some of the basic principles that, we believe, govern all processing of information in biological systems.
The usual difficulty encountered, not only in describing, but also in comprehending these principles is that it involves the appreciation of two kinds of mapping. One that allows for an internal representation of environmental features. These are represented in the structure and function of the information processing apparatus, in principle the central nervous system. The other kind of mapping concerns a representation of these internally mapped features in the form of messages composed of symbols that are remappable into the internal representations of a partner who participates in a symbolic discourse. Let me illuminate this situation with two illustrations.
Figure 2 is a schematic of the canon of perception and cognition. Since our universe is not Chaos, that is that anything can happen that could logically happen, but Cosmos where only certain things can happen according to the „Laws of Nature“ that are so beautifully, but naively, presented in textbooks of physics, chemistry, etc., „cosmic constraints“ must prohibit these pages you hold in your hands to turn suddenly into big, pink elephants that fly out through your window. These constraints manifest themselves in spatio-temporal structures, the „features“ of our environment (upper box in Figure 2). However, an organism looking at this environment cannot see the constraints. He only gets information about the environmental structures via his sensory apparatus. But since he has to make inductive inferences of what his environment will be later on, or beyond what he immediately perceives, this information is completely worthless unless — and here is the important point — he can compute the constraints that produced these structures. Hence, he shoves this information to his brain and lets it figure out the constraints. These, in turn are tested in the environment and new structural information is perceived. The terminology in this closed information loop is „perception“ for reception of structural information, and „cognition“ for this computation of constraints. I shall in a moment discuss a simple example of structure and function of a constraint computer that maps the environmental feature „containing discernible things“ into the corresponding internal representation.