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How A.I. Conquered Poker

nytimes.com

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Re: How A.I. Conquered Poker

#41

Post by JacobThreeThree »

robrenaud wrote: post #28
fdgsdfogijq wrote: post #23

Earlier quoted context omitted.

Big difference with poker is that its all about money, the game doesnt work if people arent risking something. And if computers are superior, the game breaks down.

You are worried that people will cheat in online poker, or what? For poker, people can still play face to face, and it being a game of mixed strategies means it's probably a lot less important that poker bots are better than people than in chess. Top chess players use the computers to set up preparation bombs on their opponents, with rebuttals to moves for specific positions created by the computers. That doesn't wor…

>You are worried that people will cheat in online poker, or what?

The norm for online chess is to not play for money, whereas the norm for online poker is to play for money, often for large sums.

Of course the game with higher stakes is more likely to attract cheaters.

Re: How A.I. Conquered Poker

#42

Post by redisman »

jstx1 wrote: post #29
torginus wrote: post #18

Does this mean that online poker is effectively over?

It's kind of dead-ish because there aren't big edges and most people who play online are decent enough. Online poker has been deteriorating for years (with maybe a small uptick due to the pandemic). But this article could have been written a few years ago, there's nothing new in it.

Ever since the US outlawed it it’s been dead-ish

Re: How A.I. Conquered Poker

#43

Post by paxys »

JacobThreeThree wrote: post #41
robrenaud wrote: post #28

Earlier quoted context omitted.

You are worried that people will cheat in online poker, or what? For poker, people can still play face to face, and it being a game of mixed strategies means it's probably a lot less important that poker bots are better than people than in chess. Top chess players use the computers to set up preparation bombs on their opponents, with rebuttals to moves for specific positions created by the computers. That doesn't wor…

>You are worried that people will cheat in online poker, or what? The norm for online chess is to not play for money, whereas the norm for online poker is to play for money, often for large sums. Of course the game with higher stakes is more likely to attract cheaters.

> whereas the norm for online poker is to play for money, often for large sums

That is definitely not the norm. Most people are playing recreationally. Heck it is illegal to pay poker online with real money in 44/50 states in the US.

Re: How A.I. Conquered Poker

#44

Post by jstx1 »

soferio wrote: post #39

What teaching or training tools are out there for a very average player at no limit Texas hold’em who just wants to get at bit better to a respectable level at a modest time commitment , and does not need to be a pro-level player?

Books (there's very few good ones)

Training videos

1-on-1 coaching

PioSolver (and other similar software)

For any of these to stick, you need to spend some amount of time studying by yourself; just consuming learning material and playing isn't enough.

Re: How A.I. Conquered Poker

#45

Post by JacobThreeThree »

HALtheWise wrote: post #8
hashberry wrote: post #2

> he opened a computer program called PioSOLVER, one of a handful of artificial-intelligence-based tools So I checked out this tool, and the team describes themselves as "programmers interested in algorithms"[0] ... what is the difference between A.I. and algorithms? [0] https://www.piosolver.com/pages/about-us

The taxonomy I personally use is: * Every computer program has algorithms, it's an extremely general term for "the idea behind how the computer will solve the problem". Advanced algorithms are typically those that took a lot of human effort to come up with. * Machine Learning refers to a specific class of algorithms where the computer automatically figures out (part of) what it should do based on data. * Deep learnin…

I like your framework.

Would you put statistical analysis "algorithms" in the same category as "Machine Learning"?

Re: How A.I. Conquered Poker

#46

Post by RivieraKid »

For some time I've been pondering about creating a multiplayer poker AI that would (1) play reasonably well but not at a superhuman level (2) not require expensive hardware.

Frustratingly, this seems to be an unsolved problem. Pluribus is only 6-max, requires fixed starting stack sizes and requires a lot of hardware.

Re: How A.I. Conquered Poker

#47

Post by michalsustr »

bluecalm wrote: post #9

I am the solver programmer mentioned in the article. I think it came out pretty decently. Maybe not all the details are right (I was late answering fact checking email) but I think it's a decent read and the author has done a good job!

Congrats on putting this together, it's not easy! I'm curious, what papers have you used for your implementation? I know there are a couple of reimplementations of DeepStack out there.

Disclaimer: I'm doing phd in this area, generalizing to harder games than poker.

Re: How A.I. Conquered Poker

#48

Post by tromp »

I like how the article gives examples of the sort of entropy players draw on to make their random choices:

> Koon will often randomly select which of the solver’s tactics to employ in a given hand. He’ll glance down at the second hand on his watch, or at a poker chip to note the orientation of the casino logo as if it were a clock face, in order to generate a percentage between 1 and 100.

Re: How A.I. Conquered Poker

#49

Post by bko »

noambrown wrote: post #38
jstx1 wrote: post #27

But it hasn't conquered it! I kept searching the article for some new recent breakthrough that I've missed but it's not there. Yes, solvers like Pio have been around for years and limit holdem has been essentially solved for a while but nobody plays limit holdem anyway. The two most popular games (no-limit Texas holdem and pot-limit Omaha) are still unsolved.

Bots are superhuman in no-limit Texas hold'em. Libratus beat top humans in two-player in 2017 and Pluribus beat top humans in six-player in 2019: https://www.science.org/doi/abs/10.1126/science.aao1733 https://www.science.org/doi/abs/10.1126/science.aay2400 It's shocking that the reporter didn't mention these results or anything else more recent than 2015.

The article was fascinating but honestly read like an ad for PioSolver

Re: How A.I. Conquered Poker

#50

Post by bluecalm »

michalsustr wrote: post #47
bluecalm wrote: post #9

I am the solver programmer mentioned in the article. I think it came out pretty decently. Maybe not all the details are right (I was late answering fact checking email) but I think it's a decent read and the author has done a good job!

Congrats on putting this together, it's not easy! I'm curious, what papers have you used for your implementation? I know there are a couple of reimplementations of DeepStack out there. Disclaimer: I'm doing phd in this area, generalizing to harder games than poker.

The solver was purely based on our (mine and my partner's) ideas. We tried reading some papers to find ideas to improve our solver but we had found that they are not very helpful - written in opaque language, using wrong tree representation and not focusing on practical implementation aspect. Maybe things changed since then but I haven't found anything useful at all in published papers about poker with the exception of two page one by Oskari Tammelin describing CFR+ algorithm (which we haven't used in our software because of its significant memory requirements).

We considered it very unlucky that the science paper was published as we thought more people will implement solvers then (ours was ready in mid 2014 and we released and a working solver with a GUI in early 2015, 3 months after the Limit Holdem paper). As it turned out though it didn't really matter much.

I had an idea to code a poker solver around 2008. Unfortunately I was yet to learn to code back then. The biggest challenge was to overcome implementation issues. Once I got the crucial part to be fast enough I knew the solver is possible. I think not having much background in the field allowed me to come up with more natural (and better) tree representation and memory efficient (even if not the fastest) algorithm as I was thinking more as poker player than a computer scientist back then.

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