[Computer-go] What's a good playout speed?

Petr Baudis pasky at ucw.cz
Tue Apr 7 03:56:48 PDT 2015


On Tue, Apr 07, 2015 at 12:03:12PM +0200, Urban Hafner wrote:
> Now that I have a bit of time again, what would be a good starting point to
> improve upon UCT and light playouts? RAVE definitely comes to mind, as well
> as enhancing the playouts with heuristics like the MoGo 3x3 patterns.

  Well, my suggestions would be in the form of Michi (and its git
history). ;-)

> there are any good papers on adding priors to the search tree (and where
> the underlying data is coming from)? I'm sure there must be, but I think I
> just don't know how to search for it.

  Basically, you can either do progressive widening / unpruning / bias.
The terminology is rather confusing.

  In case of progressive bias, you can either initialize the winrate
with N wins (positive bias) and M losses (negative bias) with N and M
determined by various heuristics (Fuego, Pachi, Michi use this),
or have

	(1-alpha)*winrate + alpha*bias

with bias being a "hypothetical winrate" determined by the heuristics
and alpha: 1 -> 0 as #simulations: 0 -> infty (e.g. alpha=sqrt(c/n) or
some other random formula like that).

  I know about no good survey papers personally.

On Tue, Apr 07, 2015 at 07:20:37PM +0900, Hideki Kato wrote:
> For prior values in the tree, almost(?) all strong programs use Remi's 
> method these days.
> http://remi.coulom.free.fr/Amsterdam2007/MMGoPatterns.pdf

  Do you mean all the strong programs do progressive widening?

				Petr Baudis
	If you do not work on an important problem, it's unlikely
	you'll do important work.  -- R. Hamming

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