On Tue, Oct 27, 2009 at 06:32:44PM +0200, Olivier Teytaud wrote:
> >
> >
> > AIUI, once upon N simulations in a node you take let's say the node with
> > the lowest value, pick one son of it at random within the tree and start
> > a simulation?
> >
>
> I'll try to write it clearly (for binary deterministic games, extensions can
> be shown but they are too long and out of topic in this mailing list I guess
> :-) ):
> ================
> If (average value of father < threshold )
> then
> randomly pick up one son
> else
> pick up the son with maximum score
> end
> ====================
Aha, thanks for clearing that up.
> If the score is asymptotically equivalent to the success rate, and if the
> threshold is >0 and < 1, then this ensures
> consistency (convergence to optimal move). If the score is well done, then
> this is consistent without visiting all the tree.
But is it shown that "the score is well done" for these properties to
hold in case of RAVE-guided exploration? Since it massively perpetuates
any kind of MC bias...
> > Wow - one of my planned little projects was genetic development of the
> > 3x3 patterns... To evaluate patterns, do you use tournaments or some
> > smarter method? I feared one generation would take awfully long...
> >
>
> We use a stupid method, i.e. the success rate. The pattenrs are bigger than
> 3x3, with jokers in them. Bandits (Bernstein races, slightly modified) are
> used
> for distributing the computational effort among the tested patterns.
Thank you for pointing me to more study material. :-)
--
Petr "Pasky" Baudis
A lot of people have my books on their bookshelves.
That's the problem, they need to read them. -- Don Knuth
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