Re: [computer-go] BOINC

> milestone 1: All network-nodes compute pure Monte-Carlo (no search > tree) scores for the possible moves, the scores are combined centrally > to pick the move. It's easy, it will wring out the system, and the > bandwidth is low. The playing performance will always be poor because > this algorith

Re: [computer-go] BOINC

On Tue, 30 Oct 2007, Stuart A. Yeates wrote: > On 29/10/2007, Ian Preston <[EMAIL PROTECTED]> wrote: > > G'day guys, > > I'm involved in the development of a very powerful and flexible grid > > software, which we plan to release in January. It is all java based. > > http://www-nereus.physics.ox.ac

Re: [computer-go] Where is Mogo?

Le lundi 29 octobre 2007, Don Dailey a écrit : > I don't see Mogo on the server?Where is Mogo? > > However CrazyStone is there to represent the Monte Carlo programs and > seems to be doing a very good job indeed! > > CS-8-26-2CPU is > doi

Re: [computer-go] Handicap vs Elo

Le lundi 29 octobre 2007, Don Dailey a écrit : > I don't see Mogo on the server?Where is Mogo? > > However CrazyStone is there to represent the Monte Carlo programs and > seems to be doing a very good job indeed! > > CS-8-26-2CPU is > doi

Re: [computer-go] BOINC

> -Original Message- > From: Tapani Raiko <[EMAIL PROTECTED]> > To: computer-go > Sent: Tue, 30 Oct 2007 6:39 am > Subject: Re: [computer-go] BOINC > > milestone 1: All network-nodes compute pure Monte-Carlo (no search > > tree) scores for the possible moves, the scores are combined cen

Re: [computer-go] BOINC

> -Original Message- > From: Jason House <[EMAIL PROTECTED]> > To: computer-go > Sent: Mon, 29 Oct 2007 3:00 pm > Subject: Re: [computer-go] BOINC > On 10/29/07, [EMAIL PROTECTED] <[EMAIL PROTECTED] > wrote: > > milestone 1: All network-nodes compute pure Monte-Carlo (no search tre

[computer-go] Definition for monte carlo

There has been a lot of talk about monte carlo and while I have the jist not sure exactly what it is? Would someone explain it? What I've read online is just to play a bunch of random games and pick the best one. Is there now real evaluation between the games or sorted method for generating moveme

Re: [computer-go] Definition for monte carlo

On Tue, Oct 30, 2007 at 12:43:35PM -0400, Joshua Shriver wrote: > There has been a lot of talk about monte carlo and while I have the > jist not sure exactly what it is? Would someone explain it? Here is my (amateurish) understanding: Evaluation of a go position is very difficult. Monte Carlo (MC

Re: [computer-go] BOINC

On 10/30/07, [EMAIL PROTECTED] <[EMAIL PROTECTED]> wrote: > > > > -Original Message- > > From: Jason House <[EMAIL PROTECTED]> > > To: computer-go > > Sent: Mon, 29 Oct 2007 3:00 pm > > Subject: Re: [computer-go] BOINC > > > > > On 10/29/07, [EMAIL PROTECTED] <[EMAIL PROTECTED] > wrote: >

Re: [computer-go] Definition for monte carlo

The terminology has become a little muddled. I'll use MC to mean "Monte Carlo" for the rest of this. The really good programs such as Mogo and Crazy Stone have elements of MC in them, but are not pure MC programs.I'm not even sure what "pure MC" means. But really, they are tree searchers.

Re: [computer-go] BOINC

It would be very difficult to put 1000 computers to work on a big network to produce a single instance of a strong player. There are way too many interactions - it's difficult to split the work up in a reasonable fashion. It's probably possible, but would require a lot of study. There are cert

Re: [computer-go] Definition for monte carlo

On 10/30/07, Heikki Levanto <[EMAIL PROTECTED]> wrote: > This works surprisingly well, although there are some drawbacks. > Evaluating > positions this way prefers safe, solid groups. And in the end game, when > the > result is decided, the programs play unnatural moves, since all moves lead > to

Re: [computer-go] Definition for monte carlo

Heikki's answer is close. I would think it important to add that MC is a statistical sampling algorithm, so the attempt is to simplify the difficult job of evaluating a board state by sampling a large number of random continuations, with the assumption that if enough samples are checked, you wi

Re: [computer-go] Definition for monte carlo

> When an MC bot is ahead, it'll play safe moves that help guarantee a coast to victory (many times by 1/2 point). I am surprised by how often an MC bot wins by exactly 0.5 point.It's almost as if it is converging to a 0.5 victory. One way to look at this is that an MC program is all about

Re: [computer-go] Definition for monte carlo

On Tue, Oct 30, 2007 at 01:33:07PM -0400, Jason House wrote: > I don't think MC evaluation favors stable groups. I guess I didn't really say what I meant here. MC evaluation sees weaknesses in groups that can be killed by random play, even if they are safe enough in the eyes of human players. For

Re: [computer-go] Definition for monte carlo

On 10/30/07, Heikki Levanto <[EMAIL PROTECTED]> wrote: > > > It's really a function of the perceived chances of winning. When > behind, > > it'll play bold moves since it's the only real way to win. An MC bot > that > > is behind in endgame (even if by 1/2 point) plays so wildly, it > frequently

Re: [computer-go] BOINC

On Tue, 30 Oct 2007, Jason House wrote: I think we're in agreement. I didn't know about the 5k limit, but that's essentially what I was thinking. The 5k limit is only true for "heavy" playouts (Don wrote that for 'Anchorman'). "light" playout don't plateau that early but are intrinsically weak

Re: [computer-go] Definition for monte carlo

On Tue, Oct 30, 2007 at 02:45:56PM -0400, Jason House wrote: > Similarly, I've been in won games and gotten bitten by a tesuji by the > opponent. If I had been just a bit safer in my play, I could have had a > comfortable win. Similarly, reasonable MC bots solidify the core to win > rather than t

Re: [computer-go] Definition for monte carlo

If you're ahead and go for a bigger win, generally you're just risking more to gain more when you don't need more. there is *absolutely* no advantage from a game-theoretical point of view to try to win by more than 0.5 points. and in practice, it's generally not a great idea to try to win by any

Re: [computer-go] Definition for monte carlo

On Tue, Oct 30, 2007 at 12:55:21PM -0700, steve uurtamo wrote: > If you're ahead and go for a bigger win, generally you're > just risking more to gain more when you don't need more. > > there is *absolutely* no advantage from a game-theoretical > point of view to try to win by more than 0.5 points.

Re: [computer-go] Definition for monte carlo

On 10/30/07, Heikki Levanto <[EMAIL PROTECTED]> wrote: > Of course this does not apply if one has confidence in having the game > perfectly well analysed, and will know how the game will end. Such > finesse > is seldomly seen in kyu-level human players. And computer programs are not > quite that

Re: [computer-go] Definition for monte carlo

Hi Steve, steve uurtamo wrote: > If you're ahead and go for a bigger win, generally you're > just risking more to gain more when you don't need more. > > there is *absolutely* no advantage from a game-theoretical > point of view to try to win by more than 0.5 points. and in > practice, it's gener

Re: [computer-go] Definition for monte carlo

Heikki Levanto wrote: > On Tue, Oct 30, 2007 at 12:55:21PM -0700, steve uurtamo wrote: > >> If you're ahead and go for a bigger win, generally you're >> just risking more to gain more when you don't need more. >> >> there is *absolutely* no advantage from a game-theoretical >> point of view to

Re: [computer-go] 19x19 CGOS

2007/10/30, Christoph Birk <[EMAIL PROTECTED]>: > On Mon, 29 Oct 2007, Christoph Birk wrote: > >> Of course it seems silly to have 2 of these programs play each other - > >> which could easily happen. The game might start like this: > >> > >> pass > >> pass > >> pass > >> etc. > > > > And