Life In 19x19

To counter that problem the UCT score has two parts. One is the winning probability, and one represents the which decreases as the node gets explored. And this term causes unexplored nodes to played. I think there exists a prove that MCTS gives the same results as normal minimax search when the ...

What Li Kao said. The depth changes slowly: each simulation adds 1 node to the tree (usually). So if the tree looks like this:



Sorry, I'm still not sure that UCT works good.

For example, I have a position with two possible moves (a1 and b1):

O
/ \
(a1) (b1)

First random game (using a1 as ...

Why winrate takes into account only wins?



What is better:

3 wins, 0 draws, 7 loses

or

2 wins, 6 draws, 2 loses

?

emeraldemon wrote:The most comprehensive explanation is Sylvain Gelly's thesis, where he introduces it and explains how Mogo works:

http://www.lri.fr/~gelly/paper/SylvainGellyThesis.pdf

Thanks a lot!

The questions still remain. Am I correct thinking that the program creates a tree search (with which depth, by the way) and then plays simulations for terminal nodes?

Those articles are a good starting point:
m

Thank you. I didn't understand what author of the article (Magnus Persson?) wanted to say. It seems that English isn't his native language. Or I'm not a smart guy

The sum of the winrate and the number (UCTvalue) for each candidate move n is computed ...

Hello all!
I would much appreciate if someone could explain me what exactly "upper confidence bounds applied to trees" is.

I added Monte Carlo to my engine, and now it plays even worse