[net.ai] "The Knowledge"

gordon@warwick.UUCP (04/22/86)

"The Knowledge" is a test which London taxi drivers have to pass
as part of the requirements of their profession. It is quite simply
a question of learning the streets of a section of the capital.
The method they employ is to go around the streets, learning as
they go. They do not stare at a map. Some instruction is given in
the classroom, however.
To me, this highlighted the differences in the learning process,
between a machine system and a human, rather well. Humans are not
computers or machine systems of any sort.

Gordon Joly  -- {seismo,decvax,ucbvax}!mcvax!ukc!warwick!gordon

greg@cs.hw.AC.UK (Greg Michaelson) (04/23/86)

> "The Knowledge" is a test which London taxi drivers have to pass
> as part of the requirements of their profession. It is quite simply
> a question of learning the streets of a section of the capital.
> The method they employ is to go around the streets, learning as
> they go. They do not stare at a map. Some instruction is given in
> the classroom, however.
> To me, this highlighted the differences in the learning process,
> between a machine system and a human, rather well.

So why do so many people spend their leasure hours building electronic
mice which learn their way round mazes?

gordon%euclid@euclid.UUCP (04/27/86)

In article <804@brahma.cs.hw.AC.UK>, greg@cs.hw.AC.UK (Greg Michaelson) writes
> So why do so many people spend their leasure hours building electronic
> mice which learn their way round mazes?
Ah. You do not understand the subtlety of the experiments which
the mice are performing on the scientists.
BTW, I discovered that the apprentice cabbies have to *learn* 481 separate
from a book called "The Blue Book". They are not given a street map.

Gordon Joly -- {decvax,ucbvax,seismo}!mcvax!ukc!warwick!gordon

drew%ukma@ukma.UUCP (04/28/86)

In article <275@euclid.warwick.UUCP> gordon@euclid.UUCP (Gordon Joly) writes:
>To me, this highlighted the differences in the learning process,
>between a machine system and a human, rather well. Humans are not
>computers or machine systems of any sort.
>
>Gordon Joly  -- {seismo,decvax,ucbvax}!mcvax!ukc!warwick!gordon

How is this? Humans are biological machines which happen
to have the ability to learn.  Although learning in the general
case has not been quantified, this does not mean that it cannot.

Humans are simply such weak learners that they cannot remember the
map you mention.

-- 
Drew Lawson
					cbosgd!ukma!drew
"Parts is parts."			drew@uky.csnet
					drew@UKMA.BITNET

gordon%euclid@euclid.UUCP (04/28/86)

Interesting to note that Fred Housego, a London taxi driver, won
the Mastermind final a few years ago.
(Mastermind is a "intellectual" TV quiz show in the U.K.)

Gordon Joly -- {decvax,ucbvax,seismo}!mcvax!ukc!warwick!gordon

schraith@uiucdcsb.CS.UIUC.EDU (04/30/86)

There is an article by Pierre Bierre ("The Professor's Challenge".            
  The AI Magazine, Winter 1985:60-70) which bears on this problem.

  It seems to me that if AI researchers wish to build a system which
  has any versatility, it will have to be able to learn, probably
  in a similar manner to the taxicab drivers.  Bierre states this problem:
  "Organize a symbolic recording of an ongoing stream of fly-by
  sensory data, on the fly, such that at any given time as much as 
  possible can be quickly remembered of the entire stream."
  Surely computer professionals have better things to do, ultimately,
  than spoonfeed all the knowledge to a computer it will ever need.

gordon@warwick.UUCP (Gordon Joly) (05/08/86)

I am a human being, and not a machine of any kind. I had to 
learn my multiplication tables at school. A teacher showed me
me how to add; I made up my own rules.

Gordon Joly -- {seismo,ucbvax,decvax}!mcvax!ukc!warwick!gordon

levy@ttrdc.UUCP (Daniel R. Levy) (05/09/86)

In article <5500032@uiucdcsb>, schraith@uiucdcsb.CS.UIUC.EDU writes:
>  It seems to me that if AI researchers wish to build a system which
>  has any versatility, it will have to be able to learn, probably
>  in a similar manner to the taxicab drivers.  Bierre states this problem:
>  "Organize a symbolic recording of an ongoing stream of fly-by
>  sensory data, on the fly, such that at any given time as much as
>  possible can be quickly remembered of the entire stream."
>  Surely computer professionals have better things to do, ultimately,
>  than spoonfeed all the knowledge to a computer it will ever need.

As nothing but an interested observer in this discussion (I am in no
wise an AI guru, so please forgive me if I bumble) your observation
indeed makes sense me, that an A.I. system could well do better by
"learning" than by having all its "smarts" hardcoded in beforehand.
But it also seems possible that once a computer system HAS been
"trained" in this way, it should be quite easy to mass produce as
many equally capable copies of that system as desired; just dump its
"memory" and reload it on other systems.

Any comments?  Does a "learning" system (or one that knows how to teach
itself) indeed hold more promise than distilling expert human knowledge 
and hardcoding it in?  Perhaps I've answered my own question, that the
system that can "learn" is better able to adapt to new developments in
the area it is supposed to be "intelligent" in than one which is static.
Maybe the best of both worlds could apply (the distilled human knowledge
coded in as a solid base, but the system is free to expand on that base
as it "learns" more and more)?
-- 
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gordon@warwick.UUCP (Gordon Joly) (05/20/86)

In article <283@euclid.warwick.UUCP> gordon@euclid.UUCP (Gordon Joly) writes:
>I am a human being, and not a machine of any kind. I had to 
>learn my multiplication tables at school. A teacher showed me
>me how to add; I made up my own rules.
>
>Gordon Joly -- {seismo,ucbvax,decvax}!mcvax!ukc!warwick!gordon

Word up, my human friend. They are going to teach me to touch-type!

Greetings to All Material Intelligent Beings!
from
The Joka.

Disclaimer -- These opinions are not those of my programmer,
              or the operating system in which I reside.