Are you sure you are not over-tuning to some opponent, or to self-play?  I
have a very simple formula, win rate plus rave (with the simpler beta
formula), plus the simple upper bound term.  I bias the rave simulations
only.  It seems to work pretty well.  Your description sounds pretty
complex.

 

David

 

From: computer-go-boun...@computer-go.org
[mailto:computer-go-boun...@computer-go.org] On Behalf Of Olivier Teytaud
Sent: Tuesday, September 29, 2009 1:26 PM
To: computer-go
Subject: Re: [SPAM] Re: [computer-go] Progressive widening vs unpruning

 

 

I guess I'm not really appreciating the difference between node value
prior and progressive bias - adding a fixed small number of wins or
diminishing heuristic value seems very similar to me in practice. Is the
difference noticeable?


It just means that the weight of the prior does not necessarily decrease
linearly. For example, for Rave, you might prefer to have a weight which
depends on both the number of Rave simulations and on the number of "real"
simulations. 

The formula designed by Sylvain for Rave, for example, can't be recovered
without this generalization. For the current mogo, as we have several terms
(one for the empirical success rate, one for Rave, one for patterns, one for
expert rules...), some of them with used at different places in the code
(there is a prior expressed in terms of "rave" simulations, and a prior
expressed as "real" simulations), it would be complicated to come back to
something much simpler ... but perhaps it's possible. Such a clarification
might be useful, I have no clear idea of the impact of Rave values now in
mogo, in particular for long time settings, and it's not so easy to clarify
this point - too many dependencies between the many terms we have.  

I think someone pointed out a long time ago on this mailing list that
initializing the prior in terms of Rave simulations was far less efficient
than initializing the prior in terms of "real" simulations, at least if you
have classical "rave" formulas - at least, we had an improvement when adding
a prior in the "real" simulations, but we had also an improvement when
adding one more term, which is not linear. Sorry for forgetting who :-(
Olivier



 

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