> > I could see a case where it is possible to reduce a variance of a single
> > variable even in the 0-1 case. Let us say that black has about 5% chances of
> > winning. If we could (exactly) double the chances of black winning by
> > changing the nonuniform sampling somehow (say, enforce bad move
As I have spent a lot of time trying to guess what could be done for
Quasi-Monte-Carlo
or other standard forms of Monte-Carlo-improvements in computer-go, I
write below
my (humble and pessimistic :-) ) opinion about that.
Let's formalize Monte-Carlo.
Consider P a distribution of probability. Co
Tapani Raiko wrote:
It seems that there are at least three cases:
1: Choosing a random move from a uniform distribution
2: Choosing a random move from a nonuniform distribution (patterns etc.)
3: Choosing a move taking into account what has been chosen before
The concensus seems to be that numb
It seems that there are at least three cases:
1: Choosing a random move from a uniform distribution
2: Choosing a random move from a nonuniform distribution (patterns etc.)
3: Choosing a move taking into account what has been chosen before
The concensus seems to be that numbers 1 and 2 are MC a
ivan dubois wrote:
I dont understand how you can reduce the variance of monte-carlo sampling,
given a simulation can return either 0(loss) or 1(win).
Maybe it means trying to have mean values that are closer to 0 or 1 ?
Well strictly speaking I agree the standard models don't fit that well
- t
It seems that there are at least three cases:
1: Choosing a random move from a uniform distribution
2: Choosing a random move from a nonuniform distribution (patterns etc.)
3: Choosing a move taking into account what has been chosen before
The concensus seems to be that numbers 1 and 2 are MC and
Envoyé le : Mardi, 6 Février 2007, 14h33mn 09s
Objet : [computer-go] Monte Carlo (MC) vs Quasi-Monte Carlo (QMC)
Upon continuing to learn about the general Monte Carlo field, I've found
it seems there is a general consensus in this community about a
distinction between Monte Carlo (MC) and wh
Upon continuing to learn about the general Monte Carlo field, I've found
it seems there is a general consensus in this community about a
distinction between Monte Carlo (MC) and what appears to be commonly
called Quasi Monte Carlo (QMC). MC is defined as using
random/pseudo-random distributions a
