[EMAIL PROTECTED] wrote:
Yes. Don's scalability argument states that ELO gain is proportional
to time doubling.
For me scalable use of time implies that time translates into depth.
The extra depth is:
m - m0 = log(2)/log(b).
So if the ELO gain for time doubling in Chess equals 100 over a
Hi Matt,
On 1/25/07, Matt Gokey [EMAIL PROTECTED] wrote:
But just because a rule of thumb holds for Chess doesn't mean it does
for Go. Of course I could be wrong, but I was just trying to introduce
reasonable doubt, since Don always seems so sure of himself ;-)
If I may venture trying to
On Thu, 2007-01-25 at 03:27 -0600, Matt Gokey wrote:
Learning these skills while thinking about a particular game's next
move
is not generally practical and even if possible would presumably
require
enormous extra time. Yet without this ability you are left with a
massively rapid
Go, being a matter of efficiency over one's opponent, may be even more
susceptible to improvement via many small improvements over many moves than is
chess. As long as you don't leave weak shapes behind, picking up a point here,
a point there at a slightly faster rate than your opponent will
On Thu, 2007-01-25 at 08:23 -0800, terry mcintyre wrote:
Go, being a matter of efficiency over one's opponent, may be even more
susceptible to improvement via many small improvements over many moves
than is chess. As long as you don't leave weak shapes behind, picking
up a point here, a point
Terry,
Where's the notion that through small increments, there is no reasonable path
from a house 3 bedroom house to a 10 story building? Isn't the consistency of
the assumption set around how a house is designed and built fundamentally (as
in pardigm-ally) different than that of how
On 1/25/07, Don Dailey [EMAIL PROTECTED] wrote:
I also had a difficult time producing a player that was less than
200 ELO stronger than a random player. Even a single play-out,
which seems hardly enough to discriminate between moves, is
enormously stronger than a random player.It was
ofcourse you are correct, P = 1.0 is just the random player. Obviously the
ELO as a function of P is going to be continuous. So, being really close to
P=1.0 will make for a player that is only very slightly better than random.
I think it is also interesting to consider a player worse than
I am writing my program to scale to n processors because I think that is the
direction hardware is headed. However, I think clever programming will do
more than computational power with go.
On 1/25/07, terry mcintyre [EMAIL PROTECTED] wrote:
So what would it take to get corporate sponsorship
On Thu, 2007-01-25 at 12:17 -0600, Nick Apperson wrote:
I am writing my program to scale to n processors because I think that
is the direction hardware is headed. However, I think clever
programming will do more than computational power with go.
I take the point of view that clever
That was just a statement, I have never advocated WASTING power to
help
make it clear that I believe in squeezing the most out of each cpu
cycles,
not just making some algorithm as fast as it can be but also using the
best algorithms.
I did not take your post as some kind of contradictory
Vlad Dumitrescu wrote:
Hi Matt,
On 1/25/07, Matt Gokey [EMAIL PROTECTED] wrote:
But just because a rule of thumb holds for Chess doesn't mean it does
for Go. Of course I could be wrong, but I was just trying to introduce
reasonable doubt, since Don always seems so sure of himself ;-)
If I
let's step back a bit and define terms. How do we define a linear improvement
in Go?
Would that be a linear increase in ELO points, or what?
Terry McIntyre
Want to start your own business?
Learn how on
On Thu, 2007-01-25 at 20:16 -0600, Matt Gokey wrote:
Don Dailey wrote:
You are still missing the point.
I can say the same of you.
I merely am raising a question about the assertion that doubling of
_human_ thinking time results in _linear_ improvements. I am not
claiming that there is
On Thu, 2007-01-25 at 21:44 -0600, Matt Gokey wrote:
Let me expand on this. Perhaps due to the nature of Go and
the human style learning needed to judge some moves and positions to
be
advantageous many (like 20-60+) stones out with possible interplay
between groups (a tree which cannot
On Thu, 2007-01-25 at 21:40 -0600, Matt Gokey wrote:
terry mcintyre wrote:
let's step back a bit and define terms. How do we define a linear
improvement in Go?
Don can correct me if I'm wrong,
The hypothesis is: For any player rating each doubling of thinking time
creates a rating
Hi Don,
On 1/25/07, Don Dailey [EMAIL PROTECTED] wrote:
That's the thought - due
to
the nature of go the increases might not be linear nor consistent
between players of different strengths. I hesitate to venture what
others believe, but it seems based on Ray's and Mark's and others'
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