On Thu, 2002-10-31 at 01:12, Tony Lofthouse wrote:
> In a biological brain closely associated neurons are 'generally' close
> to each other physically. Whilst, artificial nodes and links are
> generally not. 
> For me this seems to lose a whole layer of information. The patterns
> related to the interconnectedness are there but the information related
> to the spatial layout of the nodes is lost.

I'll give you a third way that breaks the dichotomy.  In our model we
use a link/node structure which is not derived from NN models.  One
property that was noticed early on is that if you built a natural 3D
model of the network all the links are short, connecting only to other
relatively local nodes.  This wasn't a designed feature, just something
that was noticed later.  The network is very dense, but always local. 
It would be hard (impossible?) to implement our model without exhibiting
this type of locality.

> It would seem that this information could be useful for both spatial
> reasoning and more general reasoning.

I'm not so sure that the locality is intrinsically useful so much as it
is that good models may exhibit locality by nature.

> Is there any value in having nodes located in a virtual n-dimensional
> space? 

Only insofar as it makes certain programming tasks and algorithms easier
to implement.

> One of the advantages that artificial systems have over biological
> systems is that the cost of long distance links/synapses is no more
> expensive that short distance connections. (Where cost is directly
> related to distance between nodes/neurons.) Is this a good thing though?
> Would a way to calculate cost of connection using distance be useful?

I don't really see a use for this.  Or at least, I would see a "cost"
for long connections to actually be a reduction in efficiency
(cognitively) for the network.  My personal inclination is to classify
this as a particular limitation of the biological implementation rather
than as something necessary for a working model.  In our model, this
would cause a modest degradation of cognitive efficiency, though it
would still be perfectly usable.

-James Rogers

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