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Hi,>>>Secondly, what is widely referred to as 'cognitive behaviour', invariably >>>reduces to publicly observable and measurable behaviours - a fact which >>>renders the qualifier 'cognitive' redundant except as a convenient >>>sub-classifier.
That above is a thesis, not a fact. Indeed, it's an important thesis which has been batted around for awhile but is still not settled. The most interesting alternative to me deals with the idea that a non-trivial high-level behavior can "emerge" out of the simple interactions of low-level behaviors. A classic example is water: hydrogen and oxygen are both gases, and a simple-minded addition of them would lead to another gas, but instead it leads to water (and a big explosion if you're not careful). Likewise, we might know what individual neurons do, but a big interconnected network of them can do other things like prove theorems or argue on USENET which are not obviously predictable from the actions of the individual neurons.
A converse to that: if we can observe the high-level behaviors of a system, we cannot necessarily predict which low-level component behaviors led to the emergence of those high-level behaviors. In other words, the cognitive needn't be reducible to the observable behaviors, because that amounts to saying that by watching the high-level behavior of an organism you can predict what the various parts of its brain were doing. We can't do that now, and it's possible that in principle it can never be done fully.
Surely this is one of the most important unanswered questions in science right now.
A Further Comment on Recent Claims in the 'Rehabilitation of Rehabilitation Literature..(1997b) http://www.longley.demon.co.uk/Workj97.pdf
http://www.homeoffice.gov.uk/rds/pdfs2/r206.pdf http://www.homeoffice.gov.uk/rds/pdfs2/r205.pdf
These ideas have been formalized in an interesting way by A. Ehresmann (a mathematician) and J.P. Vanbremeersch (a physician) in the form of "memory evolutive systems." They are attempting to capture this idea of non-trivial behaviors emerging out of the interactions of low-level components. One point they demonstrate is exactly how the interconnection of the components can lead to higher level behaviors which are not cleanly predictable unless you know those interconnections. Clearly there are important implications of that observation, since we can rarely know all the interconnections which exist among a system's components -- particularly when the system is as complicated as a brain. Others in the artificial life community, for instance Nils Baas, do similar work. There is a forthcoming special issue of the journal Artificial Life on Dynamical Hierarchies which is all about this question.
Anthony
-- David Longley
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