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computer-go: Go Devil



In my personal opinion, the estimate  that the best humans are about 1
or 2 stones from perfect Go play is way off the mark.

I don't know that  much about Go and I freely admit  it but by analogy
with Chess, which I  do know pretty well, I would like  to make a case
that humans  are quite  far away  from perfect Go  play.  This  is all
based on the  assumption that Go is more complex  for humans to master
than Chess.  I  don't know for sure that this is  true, but I strongly
suspect it is.

So the  rest of my discussion  will be an excercise  in convincing you
that humans are not nearly as  close to perfect play as we might think
in  the game  of Chess  and you  can extrapolate  to Go  if  you wish.
Unfortunately,  I have  no  proof of  any  of the  assertions I'll  be
making, but here goes anyway ...

In Chess  we have  a very mathematically  logical rating  system, that
makes it quite easy to  compare two players.  You can easily calculate
for instance, based on the ratings of two individuals, what the likely
results of a series of games will be.   

Therefore,  in principle,  all we  have  to do  is compare  Kasparov's
rating to  Gods rating  to get our  answer.  Unfortunately, we  do not
know what Gods rating is!  But maybe  we can at least set some kind of
crude lower bound on it?

One thing  we do  have a pretty  good feel  for, at least  in computer
chess, is that computers seem to improve almost linearly with depth of
search.  In fact,  there is a rule of thumb that  states about 180 ELO
rating points per ply of search (more or less.)  A few years ago, when
this was  demonstrated, it was  believed that this  linear improvement
wouldn't hold with a little more speed.  I watched the depth of search
go  up year after  year without  this happening,  and yet  many people
always  felt  we were  right  at  that  point where  further  speedups
wouldn't help.   After all,  computer were starting  to get  nearly as
good as humans!   

Although  there is  now some  evidence that  the flat  line  of linear
improvment  is starting to  curve somewhat,  it's not  that pronounced
even yet.  Of  course there are many theories  and opinions that these
studies might be flawed or that there is too much intransitivy between
computer and human games and so  on, but even if you make very liberal
allowances for these,  it's difficult to conclude that  a program like
Deep Blue is very close to playing like God.

How deep does  a computer have to go to play  like God?  Personally, I
don't think  you have  to search  the entire game  tree to  get pretty
close.  We now have endgame  databases that take really simple subsets
of  the game  of  Chess and  solves  them, effectively  giving us  the
equivalent of 50,  100, 200 or more ply  searches in these specialized
situations.   These databases  play  absolutely perfect  chess in  the
domain for which they were built.   

So if  you had a  computer capable of  searching about 100  ply (let's
make up numbers!) in fairly  simple endgames, you would have something
reasonably  close  to perfect  play.   But  since  the middlegame  and
opening still have  to happen first, even this  program will still see
many positions  that it can't solve.   However, I believe  that with a
good sound  evaluation function you might  find that a  100 ply search
would come  pretty close  to playing God-like  chess!  This is  just a
wild guess.   I think the  'curve' is already  very flat in  this area
however, and  probably a 50  ply full width  search will do  nearly as
well.

Over the years I have heard  so much (well meaning) nonsense that I am
very  skeptical of  judgments  like  this.  I  remember  the bet  that
computers would easily beat the best  humans in 10 years.  The bet was
made and lost,  and then made and lost for the  next 10 years.  Humans
are notoriously bad about judging their relative position in the order
of things and  if I were a  betting person, I would bet  my whole life
savings that an omniscient player  (especially Go Devil) could give up
MANY stones to the best living player.


Don