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]>:
On Wed, Jun 12, 2013 at 11:30 AM, David Fotland
<[email protected]
<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]
<sentmsg?mailto=mailto%3acomputer%2dgo%[email protected]>
[mailto:[email protected]
<sentmsg?mailto=mailto%3acomputer%2dgo%[email protected]>]
*On Behalf Of *Oleg Barmin
*Sent:* Wednesday, June 12, 2013 8:02 AM
*To:* [email protected]
<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]
<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
--
Nick Wedd
[email protected]
_______________________________________________
Computer-go mailing list
[email protected]
http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
