On Dec 13, 2007 2:03 AM, Harald Korneliussen <[EMAIL PROTECTED]> wrote:
> Wed, 12 Dec 2007 07:14:48 -0800 (PST) terry mcintyre wrote: > > >Heading back to the central idea, of tuning the predicted winning > rates and evaluations: it might be useful to examine lost games, look > for divergence between expectations and reality, repair the predictor, > and test the new predictor against a large database of such blunders. > > Sounds a little like Temporal Difference Learning to me. I understand > both MoGo and Crazystone use patterns, do anyone know whether they use > such machine learning techniques to assign weights to them? MoGo uses TD to predict win rates. I haven't heard of any other methods to predict winning rates. I have seen some successful stuff with predicting the next move.
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