

112th KGS Computer Go Tournament - karmakaze
http://www.weddslist.com/kgs/past/112/

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karmakaze
What I find shocking isn't only the level of play by machines, but also the
number of techniques that can be applied to achieve it. Traditionally they
were very domain knowledge based and now they tend to be hybrids. This for me
really quantified how deep into the age of AI we're in. I never expected Go to
be approched this quickly as the search space is so vast.

AyaMC (AyaBot 3d on KGS) was Aya[1] rewritten as a Monte Carlo simulation.

Many Faces of Go[2] (ManyFaces 2d on KGS) has been the strongest sold Go
program which has transitioned to using Monte Carlo Tree Search.

NiceGo19N, was Detlef Schmicker's latest version of oakfoam, using a
Convolutional Neural Network. The possibilty of using a CNN to play Go
recently been described as promising, so it is good to see one such engine
developed already. See this paper[3] for more information.

Hiratuka No Igo (aka HiraBot[4] 1d on KGS). I don't know its algorithm but its
game invitation message is "15000 playouts per move".

[1] [http://senseis.xmp.net/?Aya](http://senseis.xmp.net/?Aya) [2]
[http://senseis.xmp.net/?TheManyFacesOfGo](http://senseis.xmp.net/?TheManyFacesOfGo)
[2] [http://arxiv.org/abs/1412.6564](http://arxiv.org/abs/1412.6564) [4]
[http://senseis.xmp.net/?HiraBot](http://senseis.xmp.net/?HiraBot)

