For simplicities sake, let's say I do a pure 0-ply and 1-ply monte carlo search. If the color to move is my color, I'd expect the 0-ply search to give me a more conservative winning percentage than the 1-ply search (since I'd pick the best child rather than average the children together). Similarly, if the color to move is the enemy color, I'd expect the 0-ply results to be optimistic relative to the 1-ply results.
From what I understand of how everyone does UCT, the depth of leaves are not
the same and percentages are compared anyway. I'm assuming that this bias isn't too big since it seems that hasn't been much of an issue... The UCT bots are kicking the butts of most other bots. Does anyone have any data on just how optimistic or pessimistic the results would be? I'd like to use some heuristics that inherit winning percentages from a parent node to bias the expected winning percentage of the children nodes... and maybe pruning away portions of a search in a fixed depth monte carlo search with iterative deepening.
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