Dave Dyer wrote:
In cases where the good moves are the obvious ones,
you've found them anyway.
Ok. Here I agree.
In other cases, you prune them away.
You are not really pruning, just postponing. Of course
you may overlook moves of genius, who doesn't? But
if your probabilities are
As any incomplete search, it can blunder, but why more than any other
incomplete search?
Not worse, just not a magic bullet.
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The problem with this is that below a few ply, the probabilities are
all effectively zero. All you're really doing is enshrining the
prior probabilities used to sort the first few levels.
In cases where the good moves are the obvious ones, you've found them
anyway. In other cases, you prune
The problem with this is that below a few ply, the probabilities are
all effectively zero. All you're really doing is enshrining the
prior probabilities used to sort the first few levels.
In cases where the good moves are the obvious ones, you've found them
anyway. In other cases, you prune
On Dec 5, 2007 9:39 AM, Dave Dyer [EMAIL PROTECTED] wrote:
The problem with this is that below a few ply, the probabilities are
all effectively zero. All you're really doing is enshrining the
prior probabilities used to sort the first few levels.
Why would they be zero? floating-point types
just a link :
http://ticktockbraintalk.blogspot.com/2007/11/brain-clock-temporal-resolution-g-power.html
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The general rule (in my opinion) is that playing strength will require a huge
amount of power because that's what A.I. is. This in no way implies that
it should not be efficient or that it should foolishly squander resources
(as an internal combustion engine does.) Instead it should be
Jim O'Flaherty, Jr. wrote:
Don,
I think it is tenuous to predict, much less emphatically assert, that
just because the evidence is linear at the lower scale, it remains so
at higher scales.
This is done all the time in science!Many things in science are
considered facts that haven't
Don Dailey wrote:
So I must give up on this. I know if I do the plot again someone will
say, it only applies to depths we can currently test. Surely it
will flatten out next year when the new processors come.
I cannot answer to those arguments when no evidence is presented to back
it up
Hi Dave,
You are doing it.No matter what evidence is presented, people will
find a way to say it doesn't exist.As I mentioned earlier, the
argument was that didn't apply to chess except for the first 4 or 5 ply
- then when that didn't happen they expanded it to the first 6 or 7 and
to
My experience from doing search only with Valkyria, is that Go is not
different to Chess in the sense that each extra ply really makae a
difference. Improving evaluation almost always means that search gets
deeper in UCT-type programs. Monte-Carlo simulation + knowledge gives
a better
Seo,
All I described was the scientific method plus simple probability theory
combined with using intuition to explore unknown unknowns creatively.
For a layman's explanation into this world, see the works by Talib of
Fooled by Randomness and The Black Swan.
Not sure about your analogy
Don,
I think it is tenuous to predict, much less emphatically assert, that
just because the evidence is linear at the lower scale, it remains so at
higher scales. While it is reasonable to assume, it is not certain. I
see your point that at this time, your theory about it applying to
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