[computer-go] JCIS extended abstract

[Chaslot G (MICC)]

Dear all,


Following the example of Rémi, I would like to share with you a paper that I wrote which describe some important elements of my Go program Mango.

I submitted this paper recently to the JCIS workshop 2007. Due to the fact that it was an extended abstract, a lot of details are missing. I am now working on the full paper, which will contain much more information.

 

The extended abstract can be found here: www.cs.unimaas.nl/g.chaslot/papers/pMCTS.pdf

 

Cheers,

 

Guillaume

 

PS: To answer's Sylvain question: Modifying the probability distribution of moves in the tree was more effective in Mango than the improvement done on the simulation strategy. However, Mango simulation strategy is not as good as CrazyStone's or Mogo's one. So I guess Mango won against Mogo in the last KGS tournament because it had a better way to use domain knowledge in the Tree. 

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