As soon as we describe an entity with differing degrees of detail, we are assigning to it a hierarchical nature. In addition, we habitually presuppose the validity of assigning a synchronous nature to the resulting “model” hierarchy. For an organism, the major advantage of constructing an internal self-representational hierarchy is that resulting high level “forms” are no longer constrained to operate within the complex temporal limitations of their low-level interactions. In a computational paradigm this “hiding” of sub-scalar detail makes it possible for biological organisms to develop a mechanism for multi-temporally-scaled reactions to external stimuli.

Our current concern in this context is the transport of information between the different levels of a synchronous model hierarchy: most specifically where there are only two levels involved; a detailed “inside” and its less detailed representation from “outside”. High local-to-global (inside-to-outside) correspondence implies minimal “extra” global information content: low local-to-global correspondence implies massive “extra” global information content. The vast majority of information transported across-scale (e.g. inside-to-outside) in any hierarchical system corresponds to a transfer of order, and not of novelty. Even so, the small amount of “novelty” which is transferred is noticeable, even for single-crystalline material. Comparison of the propagation of longitudinal and shear waves through large single crystals of the group IV, II-V and II-VI materials indicates that the lattice dominates the anisotropy of the elastic properties, but that a noticeable “atomic-type” component appears.

In biological systems, reproduction of an organism is controlled by information which is transported upwards in scale, from amino acids, to DNA, to cells, … Here again, structural regularity at one level acts as a “carrier” for less regular, more specific information, up from one scale to the next. It seems to us reasonable to tentatively suggest that cross-scale information transport can only stabilize dynamic relationships between adjacent levels of a hierarchical system if a strongly ordered information “carrier” is present.

Looking into the heart of a complicated system, we often describe its pathways and their meeting points by the simple picture of a network of lines and nodes, which corresponds to a “quasi-external” picture of the system. Such a quasi-external view is indefensible if more than minimal nonlinearity is evident between the different levels of representation. We attempt an initial resolution of this problem by distinguishing between “direct” and “indirect” connections between the elements of a system, and relate the description to the Newtonian 3-body problem.

With increasing systemic complication, the number of direct links goes up as the number of elements N, while the number of indirect links goes up as the square of the number of elements, N2/2: the populations of direct and indirect character                 links co-evolve at vastly different rates, and for large nonlinear-level-transition systems indirect links dominate massively. This dissimilar co-evolution of direct and indirect relations in large systems leads ultimately to the appearance of two different independently distinguishable systemic characters. One corresponds to the “normally scientific” view, which depends on formally-rational cross-scale information transport, the other corresponds to parts of the holistic system which are inaccessible to a “normally scientific” viewpoint, and which are associated with the distributed nature of indirect relations. Complete representation of systemic interactions with an environment requires the evaluation of both of these characters: if we simply describe a quasi-externally viewed system in terms of the reductively specified interactions we miss out the majority of the system! With increasing system size, we ourselves are progressively less capable of dealing with the complication of assimilating massively local relations in increasingly more complex systems, and we begin to see the systemic whole, and not the “sum of the parts”.

We believe that this bifurcation of systemic character into dual reductive and holistic parts becomes progressively more noticeable the greater the complication of a system, and that ultimately the difference between the two characters in terms of rational accessibility has led to the conventional “split” between mind and body, where the body is naturally associated with direct “scientific” bio-systemic relations, and the mind is naturally “difficult” to understand in the context of a “normally scientific” viewpoint which presupposes that all essential systemic aspects can be related to a single localised platform.

So… is it only biological organisms that can develop a “mind/body” split, or can it occur with any large system? We can see no concrete reason why a large inanimate computational system should be incapable of developing a partially autonomous distributed high level sub-systemic computational layer. There are, however, a couple of problems. The first is that of information-processing density. The degree of autonomy attainable in a computational system depends on the total amount of information which can be processed concurrently and rapidly. For conventional formally-rational digital processors this is inevitably coupled to the size of the individual processing elements compared to the communication speed: biological systems go beyond this limitation. The second problem is that of programming a partially autonomous processor. It is reasonable to suppose that it would be virtually impossible to program the startup of an autonomous processor layer. However, nature makes available the possibility of startup by mutation, and development by learning. It may be that the best we can do is to observe carefully, and try to notice if large computational systems ever appear to develop “by accident” apparently autonomous distributed control.

We present details of a very strange evolution in a medium-sized Windows computer network.
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