Just a quickstart here, and I'm not one of the real experts, so it may contain
inaccuracies. Perhaps you already know all this, perhaps not.
The basis of many game-playing programs (like chess programs) is the minimax
(or negamax) algorithm.
It is a simple algorithm by itself and you can find a
an: [EMAIL PROTECTED] namens Nick Wedd
Verzonden: za 15-11-2008 15:48
Aan: computer-go
Onderwerp: Re: [computer-go] Monte carlo play
In message
<[EMAIL PROTECTED]>,
[EMAIL PROTECTED] writes
< Hawaiian shirt analogy snipped >
>I hope you don't feel offended. Indeed you took up a won
In message
<[EMAIL PROTECTED]>,
[EMAIL PROTECTED] writes
< Hawaiian shirt analogy snipped >
>I hope you don't feel offended. Indeed you took up a wonderful
>endeavour, but I sense that you're not quite ready to go for the summit
>today.
But Tony never expressed any interest in "going for the sum
ed. Indeed you took up a wonderful endeavour, but I
sense that you're not quite ready to go for the summit today.
Best Regards,
Dave
Van: [EMAIL PROTECTED] namens tony tang
Verzonden: do 13-11-2008 22:03
Aan: go mailing list
Onderwerp: RE: [computer-go
Tony
> Date: Wed, 12 Nov 2008 10:34:21 +0900> From: [EMAIL PROTECTED]> To:
> computer-go@computer-go.org> Subject: Re: [computer-go] Monte carlo play> > >
> I am new to programming go, could some one explain to me how a monte> > carlo
> based evalution manage
> I am new to programming go, could some one explain to me how a monte
> carlo based evalution manages to play random games by itself? ie:
> who/what is the oppoent which supplies the opposing moves which
> allows another move to be randomly played after making the initial
It is self-play, so both
