So you say that: "...I'm observing that most of the increase in level comes from the selection during exploration and only in small part from the selection during simulation.", could you elaborate at all? This is very interesting. That almost suggests it might be fruitful to use the patterns in the tree, but keep lighter playouts. - George
On Sun, Nov 16, 2008 at 10:39 PM, Mark Boon <[EMAIL PROTECTED]> wrote: > Some months ago I did several experiments with using tactics and patterns in > playouts. Generally I found a big boost in strength using tactics. I also > found a boost in strength using patterns but with a severe diminishing > return after a certain number and even becoming detrimental when using large > number of patterns (1,000s to 10,000s). Since I was using a generalized > pattern-matcher, using it slowed things down considerably. Although it > played a lot better with the same number of playouts, if I compared MC > playouts with patterns to a MC playout without patterns using the same > amount of CPU time the gain was not so obvious. Since most of the gain in > strength was gained by just a few patterns I concluded just as David that it > was probably better to just use a handful of hard-coded patterns during > playouts. > > I only recently started to do real experiments with hard-coded patterns and > so far my results are rather inconclusive. I found when mixing different > things it's not always clear what contributes to any increased strength > observed. So I'm still in the process of trying to dissect what is actually > contributing where. I found for example that a lot of the increased level of > play using patterns does not come from using them during playouts but comes > from the effect they have on move-exploration. I don't know if this is due > to my particular way of implementing MC playouts in combination with UCT > search, but moves matching a pattern (usually) automatically make it first > in the tree-expansion as well and generally I can say so far I'm observing > that most of the increase in level comes from the selection during > exploration and only in small part from the selection during simulation. > > For example, in one particular experiment using just 5 patterns I saw a > win-rate of 65% against the same program not using patterns (with the same > number of playouts). But when not using the patterns during exploration saw > the win-rate drop to just 55%. > > I still have a lot of testing to do and it's too early to draw any hard > conclusions. But I think it's worthwhile trying to distinguish where the > strength is actually gained. Better yet, finding out exactly 'why' it gained > strength, because with MC playouts I often find results during testing > highly counter-intuitive, occasionally to the point of being (seemingly) > nonsensical. > > I also think what Don was proposing with his reference-bot could be > interesting. Trying to make it play around ELO 1700 on CGOS just using 5,000 > (light) playouts. I don't know if it's possible, but I think it's a fruitful > exercise. At a time where most people are looking at using more and more > hardware to increase playing-strength, knowing what plays best at the other > end of the spectrum is valuable as well. With that I mean, finding what > plays best using severely constrained resources. > > Mark > > _______________________________________________ > computer-go mailing list > computer-go@computer-go.org > http://www.computer-go.org/mailman/listinfo/computer-go/ > _______________________________________________ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/
