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First of all, I laughed at the 20-second average per game in self-play, since I ran into the same thing and have been trying to speed up the algorithm but haven't been able to get it faster (without throwing more hardware at it).

Second, I haven't read everything, but I believe you are playing a cash-game and not tournament-style. Is that correct? If that is the case, any chance you will be doing a tourney-style version?

[For those who don't play, in cash, a dollar is a dollar. In Tourney play, the top 2 or 3 players get paid out, so all dollars are not equal, as your strategy changes when you have only a few chips left (avoid risky bets that would knock you out) or when you are chip leader (take risky bets when they are cheap to push around your opponents).]

Also, curious how much poker you folks play in the lab for "research".




We're doing cash games in this experiment. At the end of the day, this is about advancing AI, not about making a poker bot. Going from two-player to multi-player has important implications for AI beyond just poker. I don't think the same is true for cash game vs tournament.

There's a cash game almost every night at the FBNY office! I don't usually play though -- I'm not nearly as good as the bot.


> In Tourney play, the top 2 or 3 players get paid out

Or top 2 or 3 thousand... depends on the tournament but it's usually the top 15% ish.


True, I am thinking "sit and go" tournament where you would have 6 players like in this research.


Is there much to do here? ICM bots have this space covered pretty effectively.


But ICM is only a model that helps you evaluate information in the tournament, players will use it often to cap their bets or as a tipping point on a call, but I've never seen it used as a complete basis of play.




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