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by kevinwang
2446 days ago
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Hmmm I could be wrong but I believe it's not true that humans could only bet fixed sizes. Instead, the AI was only pretrained with fixed sizes and had to do some kind of live search algorithm for any size outside of those values, which could be what you're referring to. Stack sizes were reset to keep the research minimally scoped, taking stack sizes into account likely does not require a quantum leap in research. This is getting pretty off topic, but the computation could be done online. |
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I went back and re-read the pre-print here (https://www.cs.cmu.edu/~noamb/papers/19-Science-Superhuman.p...). On page 2:
> To reduce the complexity of forming a strategy, Pluribus only considers a few different bet sizes at any given decision point. The exact number of bets it consid-ers varies between one and 14 depending on the situation. Although Pluribus can limit itself to only betting one of a few different sizes between $100 and $10,000, when actually play-ing no-limit poker, the opponents are not constrained to those few options. What happens if an opponent bets $150 while Pluribus has only been trained to consider bets of $100 or $200? Generally, Pluribus will rely on its search algorithm, described in a later section, to compute a response in real time to such “off-tree” actions.
Good catch, and thanks for the correction.
Regarding the effect of stack sizes, I'm not certain on this, but my intuition is that there is some effect on perceived ranges of the other 5 players at the table if stack sizes vary. Since Facebook AI will not be releasing Pluribus code or pre-trained models/weights, we can't be certain, but things like stack-to-pot (SPR) ratio would seem to matter.
Of course, you could always make the argument that human players in a cash game can re-up/refill to the maximum buy-in whenever they're short, but that's another discussion altogether.