Vlad: > Problem is twofold: you should be able to guarantee properties of this
perceptual process (so it can't be an arbitrary emergent one), and you should be able to figure out the essense of your own perception of these concepts.
No you shouldn't be able to guarantee either language or the nature of the perceptual process.
The whole point is that they are both MEANT (or evolved) to be general, abstract and open-ended and therefore emergent.
To perceive "Vladimir" my brain must recognize him from any angle - and, if I keep seeing him, keep adding new angles, new perspectives. The "Vladimir" invariant (or as it's called, "Jennifer Aniston") cell in my brain - or any adaptive brain dealing with the real world - is an ever-growing tree with more and more particular roots. Or, to put it another way, if I am an agent with language, then the "Vladimir" symbol in my brain must become ever more complexly grounded.
Concepts/ symbols/ percepts have to be general and open-ended and emergent to deal with a complex, dynamic, changing and emergent world.
Our definitions and connotations of "human" have to keep changing - to deal with new social and cultural realities like these strange transhumanists and genetic engineering and cloning etc.
Our definitions and connotations of "Russian" have to keep changing - to deal with the fact that they are no longer politically enemies etc.
Our concepts and most common mental images of "Vladimir" have to keep changing to deal with the changing physical man.
P.S. An interesting tangential thought occurs. I have talked in the main agi group of the brain being a picture tree - an idea loosely related to , though also in some ways more complex than Hawkins' idea of the brain as a hierarchical processor. Actually "tree" is a better concept here, I think, than either "hierarchy" or "grounding" - because it expresses the truth that the brain's multilevel networks of signs (and therefore levels of meaning and sense) are continually growing - and its symbolic trees continually developing new roots. (And neural networks do look like trees).
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