IDK logic and good code hunting

At the moment I am exploring logic methods of 4 or more level boolean like thing ( So, it is a contradiction in terms, it's just an analogy. ) which is :

enum {IDK, maybe, Yes, No}

When looking at the enum I thought that perhaps I could have -0 (negative zero)[ 0x80.... ] as IDK, maybe as all to the positive numbers to largest positive=YES and then down as maybe also to the largest negative=NO.

I am doing an n-Dimensional implementation of NeHe lesson (40) ( 21 ) as a hunter with the ability to use ray tracing to define its target and a seeker that attempts to avoid the hunter and find its goal by evaluating what it sees and leaving hints for itself that would identify how to proceed with choices previously made or new. It requires two windows to implement and has the hunter and seeker window so that I can view the progress as it switches dimensions. Status on each window would describe which dimensions are in effect for viewing and a trail list that shows what choices it makes at a junction. Markov plays a role here and maybe some stochastic fishing, IDK. I am thinking it might be a good tool for `|Alice Infinity|` when searching the web.

The goal is just to implement the method and discover what happens. By using a tree like linked structure I do not need to allocate space for n dimensions, which quickly becomes absurd for partitioning the dimensions in some reasonable scale. I.E. 10 dimensions with only 10 partitions is 1010 integers or about 80 gigabytes of virtual ram on my 64 bit architecture machine. Silly.

It has something to do with discovering what is intended in an information stream that contains x* [ dimension(n) and position(n) ] n-tuple or sets that may be several dimensions deep but do not describe the full dimensional space. Thus they would have a variable amount of NULL space dimensions if I were using a linear algebra expression to infer the concept.


Automated Intelligence

Automated Intelligence
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