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I'm one of the authors of the bot, AMA
Any chance of the code being released or a cepheus style answer key being provided? http://poker.srv.ualberta.ca/strategy
I'm one of the authors of the bot, AMA
I'm one of the authors of the bot, AMA
Players face mental fatigue and have so over-learned their existing strategies that it takes time to adapt new strategies and even more time for those new strategies to become second-nature.
It reminds me of sports in a way. Teams start running a new wrinkle of offense in the NFL like the wildcat and it takes a few seasons for teams to instinctively know how to play defense correctly against that option.
I'm one of the authors of the bot, AMA
Very impressive. If my understanding of how the AI works is correct, it is using a pre-computed strategy developed by playing trillions of hands, but it is not dynamically updating that during game play, nor building any kind of profiles of opponents. I wonder if by playing against it many times, human opponents could discern any tendencies they could exploit. Especially if the pre-computed strategy remains static.
In fact, the methods we use are designed from the ground up to minimize exploitability. That's a really important property to have for an AI system that is actually deployed in the real world.
Curious, why was 100BB used for six max? If I recall right, the head ups experiment was 200BB?
I'm one of the authors of the bot, AMA
1) What were the reasons for choosing 6-handed play (assuming logistical and costs)? It would be interesting to see how the bot’s strategy would differ in a full ring game. 2) Are there any plans to commercialize the bot as a tool for training human players?
Earlier quoted context omitted.
> you don't need to adapt to opponent weaknesses to win at poker at the highest levels that may be true for limit poker, but in a no-limit tournament the best this bot could do is not lose. as the pressure increases with the blinds and the players are forced to bluff and call bluffs how does this bot avoid folding itself to death from a run of bad cards? I could see this bot doing well at cashing but I don't see how…
I couldn't find it confirmed in the primary or secondary article, but I would bet the bot is just playing cash at a fixed stack depth rather than a tournament; just like in the wild, bots are much more of a problem in online cash than online tournaments. Dynamically adjusting strategies by stack depth, number of players, and pay jumps, would probably be several orders of magnitude more complex.
In the fb article linked above.
So let me see if I understand this. I don't believe it's hard to write a probabilistic program to play poker. That's enough to win against humans in 2-player. With one AI and multiple professional human players sitting at a physical table, the humans outperform the probabilistic model because they take advantage of each other's mistakes/styles. Some players crash out faster but the winner gets ahead of the safe proba…
The bot played like 10 000 hands. There is no way that is enough to prove it's better or worse than the opponents.
More so in no-limit where some key all-ins can turn the game up side down. The variance is higher than limit or fixed, right?
I did a heads up Texas holdem fixed bot with "counter factual regret minimization" like 8 years ago from a paper I read. It had to play like 100 000 hands vs a crappy reference bot to prove it was better.
Strategy detection in so short games is probably worthless.
The edge is probably in seeing who are tired or drunk in paper poker.
Curious, why was 100BB used for six max? If I recall right, the head ups experiment was 200BB?