Pat Hayes wrote:
> >Does it really involve breakdown and analysis?
>>
>>I can program a mainframe to view a rubber ball
>>and calculate a space time coordinate where a
>>robotic arm can intercept the ball and catch it
>>after one bounce. I would have to feed in
>>numbers for constant effect of gravity, mass of
>>ball, air resistance, durometer reading of ball,
>>initial trajectory and velocity etc.
>>
>>How is it a dog can catch the ball but does not
>>process any of this? I think there is something
>>more than simple calculations.
>
> There is a very simple algorithm for catching a
> ball, which was worked out by the psychologist
> Gibson. Assume the ball is in the air coming
> roughly towards you (if not, give up). Look at
> the ball and keep it in the center of your
> vision. If the ball is moving left, run left; if
> right, run right; if upwards, run back; if
> downwards, run forward. Try to keep the ball
> stationary in your field of view. When it gets
> close enough, catch it. You don't need to do all
> the simulation with numbers. Neither does the
> robot.
>
> Now, this is a very basic algorithm, and dogs,
> people and robots can all do better than this;
> but this is the basic technique. (01)
Jeff Hawkins, in his book "On Intelligence", the book Frank mentioned, uses
the dog catching a ball example. He offers another example as well. I will
adapt it to this conversation: (02)
You might claim that a mainframe computer could calculate the new position
of each of four individuals sitting on a waterbed after a fifth one climbs
on board. You would have to feed it numbers about the weight of each of the
five participants, the force of gravity, the stretchiness of the plastic,
etc. (03)
Or you could come along and say there is a very basic algorithm for
adjusting the position of people on a waterbed when an additional person
climbs on. As the new weight depresses the plastic in the location of the
fifth person, simultaneously move water out from under the new person and
put it under the four that are already there, etc. (04)
Hawkins' point, as I understand it, is that neither calculation nor
algorithms are needed to explain how a waterbed adjusts to changing
conditions. But further, that they are not necessary to explain how dogs or
people learn how to catch balls. And he goes even further, he claims that
this ability is due to the way brains, the cortex in particular, are
constructed and operate, as it is with the waterbed. But he doesn't stop
there, he also claims that progress in getting machines to due similar
tasks has been severely hampered by the erroneous belief that algorithms and
calculation could somehow reproduce the functionality of the cortex. (05)
I think this is relevant to ontology and logic both when it comes to the
ability to choose and interpret symbols to use to identify the things about
which the ontology and logic are about. (06)
John Black
www.kashori.com (07)
> Pat Hayes
>
>>Duane
>>
>>
>>On 8/6/07 1:57 PM, "Kathryn Blackmond Laskey" <klaskey@xxxxxxx> wrote:
>>
>>XML, RDF, OWL, etc. are all human
>>interpretations of trying to break down data
>>representation in such a way that they mimic
>>what the brain can do, in a highly simplified
>>manner, in hopes of allowing machines to perform
>>the basic work that a brain can.
>>
>>
>>Flying birds gave humans an existence proof that
>>flight was possible. However, attempts were
>>unsuccessful to build flying machines that
>>worked the way birds do. Eventually we achieved
>>flight by understanding aerodynamics and
>>propulsion well enough to build machines that
>>worked, even though the mechanism was quite
>>different from that used by birds. Similar
>>remarks apply to cameras, and to information
>>processing systems.
>>
>>K
>>
>>
>>
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