Can you point us to a description of the game? It would be easier to have an intelligent discussion about the game if we knew the rules...
On Wed, Jun 12, 2013 at 3:33 PM, Oleg Barmin <[email protected]> wrote: > > For quality assessment, play many games against one or more reference > opponents. > It's difficult to assament algorithm with a game against humans. The game > is young and there are no recognized masters at the moment. So it's very > hard to find human-opponent with a really good game skills. > > > With card games you can get some serious intransitivity, rocks, paper, > scissors type of stuff. > The aim of this game is to max your scores. Each turn you need to select > one of three choices. Each choice has an expectation value of your scores. > Optimal strategy here is to select a choice with max expectation value. But > it will take a years to calculate an expectation value at the start of the > game. So the game has no such intransitivity as rocks, paper, scissors. > At the last turns we can make a complete choice enumeration and calculate > an exact scores expectation value ( does go algorithms use the same > technique? ) . It's not the way for the first half of the game. But the > first half is more important. > > Oleg > > > Среда, 12 июня 2013, 14:24 -04:00 от Don Dailey <[email protected]>: > > > > On Wed, Jun 12, 2013 at 11:30 AM, David Fotland > <[email protected]<https://e.mail.ru/sentmsg?mailto=mailto%3afotland@smart%2dgames.com> > > 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]<https://e.mail.ru/sentmsg?mailto=mailto%3acomputer%2dgo%[email protected]>[mailto: > [email protected]<https://e.mail.ru/sentmsg?mailto=mailto%3acomputer%2dgo%[email protected]>] > *On Behalf Of *Oleg Barmin > *Sent:* Wednesday, June 12, 2013 8:02 AM > *To:* > [email protected]<https://e.mail.ru/sentmsg?mailto=mailto%3acomputer%[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]<https://e.mail.ru/sentmsg?mailto=mailto%3acomputer%[email protected]> > http://dvandva.org/cgi-bin/mailman/listinfo/computer-go > > > > > Best regards, > Oleg Barmin. > > _______________________________________________ > Computer-go mailing list > [email protected] > http://dvandva.org/cgi-bin/mailman/listinfo/computer-go >
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