On 12/06/2013 23:08, Don Dailey wrote:
I don't quite see the point. The goal is to find the best possible
hand YOU can make with your 13 cards and there is no betting, so I see
no point in using Monte Carlo here.
What am I missing?
Is it whether to sacrifice one of the 3 hands to strengthen the other 2?
Or in the case of a really bad hand to at least make 1 really strong
hand?
In the "open" version, you can see what hands the other players are
constructing, and act accordingly.
Also, you have to start allocating your cards to hands before you have
seen all 13 of them.
Nick
Don
On Wed, Jun 12, 2013 at 6:03 PM, Jason House
<[email protected] <mailto:[email protected]>> wrote:
For a particular breakdown into 3 hands, it should be possible to do
a monte carlo simulation by randomly distribute the remaining cards
to the other players and then randomly separating each player's
cards into 3 hands. A node in the search tree would be scored as the
average result of many simulations.
I can think of a few ways to build a search tree. If you have
experience in the game and know a few general strategies, they will
likely be very handy for achieving enough strength to evaluate the
approach. The search tree should be able to give feedback on which
strategy is best. The same strategies may also help improve the
random opponents, but that might require more care. It's easy to
introduce bias.
Sent from my iPhone
On Jun 12, 2013, at 4:06 PM, Oleg Barmin <[email protected]
<mailto:[email protected]>> wrote:
Sure. It's open chinese poker:
http://www.pokerlistings.com/poker-rules-chinese-poker
Среда, 12 июня 2013, 20:57 +01:00 от Nick Wedd <[email protected]
<mailto:[email protected]>>:
On 12/06/2013 20:33, Oleg Barmin 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.
Can you give a link to the rules of this game? Or even just
tell us its
name?
Nick
>
> Oleg
>
>
> Среда, 12 июня 2013, 14:24 -04:00 от Don Dailey
<[email protected]
<https://e.mail.ru/sentmsg?compose&[email protected]>>:
>
>
>
> On Wed, Jun 12, 2013 at 11:30 AM, David Fotland
> <[email protected]
<https://e.mail.ru/sentmsg?compose&To=fotland@smart%2dgames.com>
> <sentmsg?mailto=mailto%3afotland@smart%2dgames.com
<http://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?compose&To=%2acomputer%2dgo%[email protected]>
> <sentmsg?mailto=mailto%3acomputer%2dgo%[email protected]
<https://e.mail.ru/sentmsg?compose&To=sentmsg%3fmailto%3dmailto%253acomputer%252dgo%[email protected]>>
> [mailto:[email protected]
<https://e.mail.ru/sentmsg?compose&To=computer%2dgo%[email protected]>
> <sentmsg?mailto=mailto%3acomputer%2dgo%[email protected]
<https://e.mail.ru/sentmsg?compose&To=sentmsg%3fmailto%3dmailto%253acomputer%252dgo%[email protected]>>]
> *On Behalf Of *Oleg Barmin
> *Sent:* Wednesday, June 12, 2013 8:02 AM
> *To:* [email protected]
<https://e.mail.ru/sentmsg?compose&To=computer%[email protected]>
> <sentmsg?mailto=mailto%3acomputer%[email protected]
<https://e.mail.ru/sentmsg?compose&To=sentmsg%3fmailto%3dmailto%253acomputer%[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.____
>
>
> _______________________________________________
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>
>
>
>
> Best regards,
> Oleg Barmin.
>
>
> _______________________________________________
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--
Nick Wedd
[email protected]
<https://e.mail.ru/sentmsg?compose&[email protected]>
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Oleg Barmin.
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