I guess that the point is that this bit of evidence doesnt support either
'side' of the argument, perhaps it suggests that the argument is set up
wrong - In real social systems where the hot dog stand is, the spatial
configuration of the environment, the location of the lecture theatre and
the of the sign posts are all outcomes as well as shapers of the social
processes we are observing.In this situation the process of evolution of
the whole set of behaviours and the 'contraints' are interconnected and we
can no longer treat the the behaviour as a black box with the attractors as
constraints and outside the system. The result of evolution in this kind of
context is that the state of the whole environment moves towards attractors
in the surface, which tend to be characterised by various correlations
between properties - eg the shops on the main streets attracted by passing
trade then attract people as destinations in themselves - where since
everything reinforces everything else through feedback  there is great
stability and predictability. This I think is the really surprising thing
about social systems - how predictable and 'knowable' they are in spite of
their apparent complexity and the number of variables involved.

Perhaps this is what Kathleen meant by 'embedded'.

My memory of the Kaufman experiments was that essentially he was working
with uncorrelated variables - and so what you say would hold fine, but
might not be particularly useful for the kind of social systems I am
describing - but the again my memory is hazy :-)

A question. I have heard geographers and statisticians treat
'autocorrelation' as a 'problem'. It seems to me that autocorrelation is a
fact of urban systems and social systems in general and is probably a
'solution' to large and complex dynamic systems - does anyone know of any
good treatments of this in the literature?

>Alan Penn wrote:
>> The problem with this example is that way that observed populations of real
>> people move through space has been found to be highly regular (the patterns
>> repeat from day to day) and predictable (they are dependent on a relatively
>> limited set of factors defining the physical configuration of the spatial
>> system being considered). Incidentally, the characteristics of spatial
>> variations in people movement are quite different to those for a gas, and
>> the analogy clearly does not hold.  If anything people are more predictable
>> than gases where, for instance, turbulence is still on the edge of what can
>> be predicted.
>
>The point was not how easy the simulation problem was, but that it did
>*not* necessarily become easier with increasing constraints.
>
>> The main difference as I see it is that people are 'rational' at least to
>> some degree, where gas molecules are not. One piece of evidence to back up
>> this notion is that in spatial configurations that are highly unintelligble
>> (lacking in correlations between local and global configurational
>> parameters) the predictability of movement from configuration is also
>> reduced. In other words, as you reduce the potential for rational decisions
>> to be made by making the environment unintelligible the behaviour of the
>> population appears to become less predictable.
>
>It is not clear to me which side of the argument this 'fact' supports.
>Clearly when constraints are approach being total (i.e. only one action
>is possible) then this can increase the predictability (e.g. one
>signposted route to the lecture theatre), but that is not the general
>case.
>
>Prehaps a clearer case in support of my argument is Kaufmann's NK model
>of genetic search via bit-mutation, a hillclimber's route through the
>network will be far easier to predict with K (the number of mutual
>constraints on the bit string) small than when it is large.
>
>Regards.
>
>--------------------------------------------------
>Bruce Edmonds,
>Centre for Policy Modelling,
>Manchester Metropolitan University, Aytoun Bldg.,
>Aytoun St., Manchester, M1 3GH. UK.
>Tel: +44 161 247 6479  Fax: +44 161 247 6802
>http://www.cpm.mmu.ac.uk/~bruce


________________________________________________
Alan Penn
Director, VR Centre for the Built Environment
The Bartlett School of Architecture and Planning
1-19 Torrington Place  (Room 335)
University College London, Gower Street, London WC1E 6BT
tel. (+44) (0)171 387 7050 ext 5919   fax. (+44) (0)171 916 1887
mobile. (+44) (0)411 696875
email. [log in to unmask]
www.   http://www.vr.ucl.ac.uk/
________________________________________________




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