On Wed, Jun 12, 2013 at 11:30 AM, David Fotland <[email protected]>wrote:
> For quality assessment, play many games against one or more reference > opponents. > Especially for a game that is not a game of perfect information such as go or chess. With card games you can get some serious intransitivity, rocks, paper, scissors type of stuff. Don > **** > > ** ** > > David**** > > ** ** > > *From:* [email protected] [mailto: > [email protected]] *On Behalf Of *Oleg Barmin > *Sent:* Wednesday, June 12, 2013 8:02 AM > *To:* [email protected] > *Subject:* [Computer-go] algorithm quality assessment**** > > ** ** > > Hi, everybody,**** > > I am working at the development of a cards game algorithm using MCTS. > Technically, the game model is expect minmax tree search, where direct > search takes up too much time, that is why I decided to use MCTS.**** > > The issue of using MCST, like any other approximation algorithm is its > quality assessment. I am developing an algorithm for a game where no > recognized masters exist. How do you think, guys, if for instance Go (or > Amazons) provided no way to assess an algorithm playing with professional > gamers (or other programs), how would you assets its quality?**** > > My second question: I have not yet learned Go in and out, however in my > opinion, any search of a next step should identify a number of options with > similar or even the same assessment. How do you resolve this issue?**** > > > Best regards, > Oleg Barmin.**** > > _______________________________________________ > Computer-go mailing list > [email protected] > http://dvandva.org/cgi-bin/mailman/listinfo/computer-go >
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