Hmm, sounds like I should experiment some more. Thanks! Erik
On Thu, Feb 7, 2008 at 1:11 AM, Hideki Kato <[EMAIL PROTECTED]> wrote: > Hi Erik, > > My program is very based on MoGo's report and the paper. Yes, I > used FPU of 1.15. > > -Hideki > > Erik van der Werf: <[EMAIL PROTECTED]>: > > > >Hi Hideki, > > > >Your results look similar to those of Mogo as reported in their icml > >paper. When you ran this experiment, did you use anything like FPU or > >progressive widening, or did you use Levente's original design which > >always selects unvisited moves first? > > > >Regards, > >Erik > > > > > >On Wed, Feb 6, 2008 at 3:42 PM, Hideki Kato <[EMAIL PROTECTED]> wrote: > >> I found some data. GGMC Go v2r6, against GNU Go 3.7.10 level 10, 9x9, > >> komi 7.5, 3000 playouts/move, 2000 games match: > >> > >> Without RAVE: winning rate was 23.1 +- 0.9% (-209 +- 9 ELO) > >> With RAVE: winning rate was 65.3 +- 1.1% (+110 +- 8 ELO) > >> > >> Though this includes some other improvements, most come from RAVE. > >> Unlike MoGo, my best 'K' was 1000. > >> > >> Following is my implementation of RAVE for GGMC v2r6. > >> 1) Each playout returns the score and all moves with colors played. > >> 2) While back-propagating the value (degitized score), computes the > >> mean and the variance according to UCB1 and do the same for RAVE > >> seperatelly. For RAVE, the values of all (legal) moves, except played > >> one, in a node are updated. > >> 3) In the computation of values for RAVE, the point is that there > >> appeares three colors (as someone, I remember GCP, mentioned before). > >> If the players' colors aren't the same then skip. Count the value as > >> is or negate (1 - score, for me), depending on the color of the player > >> at the position and the color for the score. > >> 4) Before back-propagating the value of each playout, I setup a color > >> table for all intersections of the board for speed-up, in fact > >> (initialized with EMPTY). That is, fill the board (table[move] = > >> color) by tracing the moves and the colors returned by the playout > >> forward (from leaf node to end of the game). Then, by tracing the > >> path from root to the leaf node, clear the table[move] (table[move] = > >> EMPTY), in order to avoid duplicate counting with UCB1. > >> 5) While descending the tree, merge the values come from UCB1 and > >> RAVE with 'K' according to the formula in the paper. > >> > >> #Though I'm writing this by reading my source code, this description > >> may include some errors. > >> > >> Hope this helps, > >> > >> Hideki > >> > >> Gian-Carlo Pascutto: <[EMAIL PROTECTED]>: > >> > >> >> I also implemented RAVE in Mango. There was a few points of > improvements > >> >> (around 60 Elo points with gnugo as reference), but as much as in the > >> >> paper of Gelly and Silver :( (around 250 Elo points if I remember > well) > >> >> > >> >> It might be that the effect of RAVE depends a lot on the simulation > >> >> strategy. Indeed, sometimes my RAVE was playing very good moves but > also > >> >> very bad ones. > >> > > >> >I don't think the simulation strategy is the key. > >> > > >> >I suspect the improvement is largest when you don't do progressive > widening. > >> > > >> >Nevertheless it would be quite interesting to see the implementation > >> >details of ggmc's RAVE. RAVE performance is quite dependent on exact > >> >implementation and parameters. > >> -- > >> > >> [EMAIL PROTECTED] (Kato) > >> _______________________________________________ > >> > >> > >> computer-go mailing list > >> [email protected] > >> http://www.computer-go.org/mailman/listinfo/computer-go/ > >> > >_______________________________________________ > >computer-go mailing list > >[email protected] > >http://www.computer-go.org/mailman/listinfo/computer-go/ > -- > [EMAIL PROTECTED] (Kato) > _______________________________________________ > computer-go mailing list > [email protected] > http://www.computer-go.org/mailman/listinfo/computer-go/ > _______________________________________________ computer-go mailing list [email protected] http://www.computer-go.org/mailman/listinfo/computer-go/
