Hi Ingo,
Thanks, yes I see it is good to keep it simple to begin with, not least,
to encourage entrants that it is not a big hurdle.
Due to the lack of definite answer to "what epsilon?" the core idea was
simply that if you keep epsilon small, then the restriction you made
about only displac
If this catches on, perhaps the rules will be referred to as the
Ingo rules ;-)
Since this is based on a real world variant of Go, why not base
epsilon on that? The fact that the limit of displacement from the
intended position is limited to the immediately
You have to be careful what heuristics you apply. This was a
surprising result: using a playout policy which in itself is a
stronger go player can actually make MCTS/AMAF weaker. The reason
is that MCTS depends entirely on accurate estimations of the value
of each
One list of go specific papers can be found here:
http://www.citeulike.org/group/5884/library
Of course you will also need tools for writing software.
On 26-Sep-15 16:24, Gonçalo Mendes Ferreira wrote:
http://senseis.xmp.net/?ComputerGo
On 26/09/2015 16:23, Cai Gengyang wrote:
Hello Compute
Thanks - looks like a bit of a goldmine.
On 06-Sep-15 11:39, Erik van der Werf
wrote:
http://www.citeulike.org/group/5884/library
___
Computer
Hi,
Good news. There are a variety of open source projects out there,
including both complete programs (Fuego, Pachi) as well as libraries to
build your own Go engine (libEgo). There are also a wealth of papers
explaining the theory behind the top algorithms. Try googling "AMAF
algorithm" or
I suspect some people may not be curious enough to follow the link, but
may be intrigued if they saw the code...
#define S W*W
#define A B.s[1]-B.s[2]-K
#define F(x,l)for(x=0; xL{ L{ C h[4],p,l; } M[S]; C b[S],c,u[S],i[S],I,p,J,s[3]; } B,F; g; Z; m;
i; e[S][4]; a[S][4]; E; J=2;
char T[9]; long
