doowwwwnnnn....below.
Mike Tintner wrote:
Colin:
others such as Hynna and Boahen at Stanford, who have an unusual
hardware neural architecture...(Hynna, K. M. and Boahen, K.
'Thermodynamically equivalent silicon models of voltage-dependent ion
channels', /Neural Computation/ vol. 19, no. 2, 2007. 327-350.) ...and
others ... then things will be diverse and authoritative. In
particular, those who have recently essentially squashed the
computational theories of mind from a neuroscience perspective- the
'integrative neuroscientists':
Poznanski, R. R., Biophysical neural networks : foundations of
integrative neuroscience, Mary Ann Liebert, Larchmont, NY, 2001, pp.
viii, 503 p.
Pomerantz, J. R., Topics in integrative neuroscience : from cells to
cognition, Cambridge University Press, Cambridge, UK ; New York, 2008,
pp. xix, 427 p.
Gordon, E., Ed. (2000). Integrative neuroscience : bringing together
biological, psychological and clinical models of the human brain.
Amsterdam, Harwood
Colin,
This all looks v. interesting - googling quickly. The general
integrative approach to the brain's functioning is clearly v. important.
A Distinctive Paradigms/Approaches. But are any distinctive models or
more specific paradigms emerging? It isn't immediately clear why AGI
has to pay special attention here. Can you do a bit more selling of
the importance of this field.
I can't overstate the importance of the integrative biology approach.
There are properties in the electrodynamics of whole collections of
brain material *which have nothing to do with connectionism*, but are
intimately and critically involved in the regulatory processes of
learning. They appear in NO current models of the brain. They are
visible in the brain when treated as an excitable cell syncytium and
involve _all of it_...astrocytes are just as important (maybe more so)
as neurons. And this includes all forms of connectivity: radiative,
conductive and via gap junctions, endocrine/genetic regulation You do
not get this story unless you treat the whole matter hierarchy as a
single unified system in all its contexts. Integrative neuroscience is
the banner under which this kind of work will tie it all together into
one story.
B Models - I notice some researchers are developing models of the
brain's functioning. Are any worthwhile? I called here sometime ago
for a Systems Psychology and Systems AI, that would be devoted to
developing overall models both of the intelligent brain and of AGI
systems. Existing AGI systems like Ben's offer de facto models of what
is required for an intelligent mind. So it would be v. valuable to be
able to compare different models, both natural and artificial.
There are so many different folks trying so many different approaches to
brain models/intelligent behaviour/cognition... the only guide I can
give is that those that are dealing with what is actually there: the
reality of brain material from a QM/cell biology upwards viewpoint, are
the only ones on the real path to a complete picture of intelligence.
Anyone that stops their explorations at some point in the past (say with
connectionism or some other abstraction) and then dives out of the
biology with a pet abstraction and starts exploring that avenue alone,
has impoverished their view of intelligence and is operating on an
assumption which is open to criticism in a bio-world where nobody can
claim to have all the answers yet. COMP was an early version of this
process. Connectionism/Neural nets was the 80s/90s flavour of the same
thing. Now we are finally getting to whole picture: dynamical systems
and brain electrodynamics. Walter Freeman's camp is the most
developed...although all he's attacked empirically is the olfactory
bulb! So if you must have somewhere to go...he's the man. "Many-body
quentum electrodynamics" is the key phrase.
My current research is operating at the computational chemistry level.
Major holes in knowledge operate even at this most basic atomic level.
As a result I know that all models around the world are a-priori
impoverished and therefore open to critical defeat i.e. I can support
no-one in their claims as to their model as a trajectory to real AGI. I
am doing my research precisely because of the impoverishment.
C Embodied Cognitive Science. How do you see int. neurosci. in
relation to this? For example, I noted some purely neuronal models of
the self. For me, only integrated brain-body models of the self are valid.
Self emerges implicitly through embodiment and situatedness. These are
not optional because specific physics is inherited by that very
situation. Model it and the physics is gone, along with intelligent
behaviour. In my (a Elk theory of consc.!) model, the concept of self
is so far of no design value. In cog sci generally studying it as a
phenomenon hasn't lead anywhere useful (that I can build). In a science
where 'first person' is an explanatory pariah, the needed fundamentals
are missing from the toolkit...I don't expect any sense to come from
anywhere. An entity with a P-conscious (occipital/visual scene)
projected depiction of the external world automatically places a self
(the projector) inside it and 'self' becomes the same as everything
else: something about which knowledge is accrued, from which behaviour
may emerge. There are heaps of papers on the self. I read them, but they
tell me nothing I can build.
D Free Will. An interest of mine. I noted some reference that
suggested a neuroscientific attempt to explain this (or perhaps
explain it away). Know any more about this?
Free Will and Free Won't(my favourite!) are high level aspects which I
don't have a clear story on just yet. I am focussed on the lower levels
entirely. When that is consolidated I will have something cogent to say.
I'd rather study it later empirically with the chips I want to build.
The motivation for my AGI to do anything at all remains problematic...I
have my ideas but it's early days...FW is an important idea, but I can't
explicitly 'build it', so it's not an early design issue. As with most
other aspects of cognition I suspect that FW is a high-level (organism
level) emergent property which has its ultimate basis in quantum
mechanical randomness/indeterminacy. My chip architecture will
incorporate the entire causal chain, thus inheriting the same
indeterminacy, so at this stage theres nothing much more for me to add.
One day.
- - - - - - - -- - - - -
Not terribly satisfying. I know. There's no quick route through the
information.
The only guide I can give is that there is a 'trump card' approach that
clears nomothetic dross like a hot blade through butter: /Base your AGI
on an "artificial scientist" model/. The clarity that emerges is
stunning, and it's all empirically testable.
regards,
Colin Hales
-------------------------------------------
agi
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