I believe we used a uniform random policy (only "don't play in your
own pseudoeyes").
The numbers probably won't be the same, but we've certainly replicated
the qualitative improvement with version 6.05 of Orego, available here:
https://webdisk.lclark.edu/drake/orego/
Peter Drake
http://www.lclark.edu/~drake/
On Jun 23, 2009, at 9:24 AM, Christian Nentwich wrote:
Peter,
I tried to reproduce this, so I gave this a whirl and the win rate
against UCB-Tuned1 with first move priority of 1.1 (like Mogo) was
only 33%. That was using uniform random playouts.
What was the playout policy you used for this?
Christian
On 18/06/2009 21:04, Peter Drake wrote:
An improvement on the UCB/UCT formula:
Stogin, J., Chen, Y.-P., Drake, P., and Pellegrino, S. (2009) “The
Beta Distribution in the UCB Algorithm Applied to Monte-Carlo Go”.
In Proceedings of the 2009 International Conference on Artificial
Intelligence, CSREA Press.
http://webdisk.lclark.edu/drake/publications/BetaDistribution.pdf
Peter Drake
http://www.lclark.edu/~drake/
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