We can use these two concepts to discuss the basis for truth engineering and to look at oops related to improper handling.
We use 'must' in the sense of knowing that something is true or false. There is a larger set of unknowns, as in 'may' be true or false. We know that 'may' is much larger than 'must' (ignoring big 'T' issues, for now, and allowing some hierarchy of unbounded sets) just from our experiences.
These sets, must and may, can be subsumed by overlaying with reals, that is we can take 1.0 as true and 0.0 as false. We, then, have that large collection in between.
Of course, this concept applies in a computational context. Not many run around with a world view based upon the reals. Not without some gizmo for handling the numbers. What we see in the modern world is that computation, and abstraction, are overlaying reality.
Such is progress, but we need to get this right, folks.
As we have already mentioned, various issues come to fore with the modern way of doing things, such as map-territory misconstruing and much more. We need to change our ways, somewhat, and do more than just stress critical thinking.
You see, no amount of critical thinking will offset undecidability and the overly complex nature of the world. Now, creativity does help.
For some, there is fear that comes from not knowing. What manager (politician) wants to talk in terms of 'may' when the audience (like the vultures of capitalism) want to hear certainty.
Granted, the problems that will be looked at are related to logic, computing, and applications thereof. That is, the modern mind and its models are the core issue. Some people seem to be beyond the types of limitations that need to be discussed, yet whether they are, or not, is itself an open-ended issue (big T).
Sure, we like to see the confident. Success in the world does point to some type of knowing. That the gaming (chimera) has adapted itself to optimize types of insights (that is, insider views, arbitrage positions that are 'must' (and ought to be a public good/debt) yet have been privatized, and more -- we can enumerate these).
So, what's the issue here? Well, an ACM paper (Intro, Article) discusses static analysis of a program and suggests means to do so successfully. The basic problem is NP-complete so cleverness is in order. Yet, the creative moves have their costs and undesirable effects.
In essence, it's not impossible to do this type of proof, just very hard. And, when done, the results are conditioned upon several things.
That ought to give us pause about planning for the future and for doing large projects. Let's take the discussion over to the FEDaerated context.
09/27/2010 -- Capitalism is for the good of us, let's bring that forward.
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