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Notes from Chapter Four *<*>
Our scientific challenge is to see both computational visualization and human perception within the same paradigm. This may not be so difficult. A large amount of experimental research exists and some of this has been integrated into our explanatory framework, stratified theory, as discussed in Foundations. *<*>

With stratified theory we see new computational projection schemes based on situational semantics. The object of visualization might be related to a concept space.  And the visualization may be controlled within the tri-level architecture (see previous chapters) so that as the visualization occurs it is possible to allow the environment to make small perturbations in the event representation.  The computed schema is altered by the perturbations, and the changes maybe used in a re-inforcement mechanim such as a neural network architecture. 

The study of the literature suggests that the human brain achieves the formation of concepts through a distributed disassembly and reassembly of representational features (Figure. 7). The explanatory framework is illustrative of a general systems property regarding the emergence of operational wholes within ecosystems. Reassembly involves the emergence of function within an ecosystem.   It is also suggested that the human in vitro concept space is a virtual space in the sense that the space does not actually ever exist in total in any specific circumstance. Awareness is not retrieved, it is constructed.

Parts of this virtual space come into being while other parts are blocked by various types of competitive cooperative network dynamics. Of course, this simple architecture disguises the complexity of how the brain uses both its neural architecture and its chemical composition.


Unified Logical Vision figure

Figure 7: The niches in ecosystem share in the common use of a finite class of natural type.
Machine intelligence based on stratification might be far simpler than human intelligence and yet share behavioral features.  For example, projection from a complete enumeration of a knowledge engineering type concept space can be made onto a concept subspace.  This might be called an interpretation space. Such a subspace may be mirrored by activation of components of a situational model supporting automated reasoning.