Vladimir Nesov wrote:
I have a doubt about role of stochastic variance in this parallel
terraced scan as it proceeds in humans (or could proceed with the same
functional behavior in AIs). Could it be that low-level mechanisms are
not that stochastic and just compute a 'closure' of given context?
Closure brings up a specific collection of answer-candidates, and if
they are unsatisfactory or if there is time to contemplate some more,
deliberation level slightly changes a context by introducing
particular bias in it, so that 'closure' gives a different set of
answers.
Effectively, this process is separated on two levels, where low-level
process doesn't work stochastically, and high-level process messes
with initial conditions on low-level process, using some kind of
ad-hoc pseudorandom generation of biases (for example, based on
collection of simple procedures that iterate on available concepts).
It certainly feels this way introspectively, and I'm not sure how it
can be determined experimentally, probably by delays between phases of
this process.
You are asking good questions about the mechanisms, which I am trying to
explore emprically. No good answers to this yet, although I have many
candidate solutions, some of which (I think) look like your above model.
I certainly agree with the sentiment that not *all* of the process can
be as fluid as the higher level parts (if that is what you are meaning).
Richard Loosemore.
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