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What took you so long? I mean not the Pluribus team specifically, but Poker AI researchers in general.

The desire to master this sort of game has inspired the development of entire branches of mathematics. Computers are better at maths than humans. They're less prone to hazardous cognitive biases (gambler's fallacy etc.) and can put on an excellent poker face.

As a layperson who's rather ignorant about both no-limit Texas hold 'em and applicable AI techniques, my intuition would tell me that super-human hold 'em should have been achieved before super-human Go. Apparently your software requires way less CPU power than AlphaGo/AlphaZero, which seems to support my hypothesis. What am I missing?

Bonus questions in case you have the time and inclination to oblige:

What does this mean for people who like to play on-line Poker for real money?

Could you recommend some literature (white papers/books/lecture series/whatever) to someone interested in writing an AI (running on potato-grade hardware) for a niche "draft and pass" card game (e.g. Sushi Go!) as a recreational programming exercise?

I think it took the community a while to come up with the right algorithms. So much of early AI research was focused on beating humans at chess and later Go. But those techniques don't directly carry over to an imperfect-information game like poker. The challenge of hidden information was kind of neglected by the AI community. This line of research really has its origins in the game theory community actually (which is why the notation is completely different from reinforcement learning).

Fortunately, these techniques now work really really well for poker. It's now quite inexpensive to make a superhuman poker bot.

So will this be the end of online poker?

It's pretty easy for good players to recognize other good players. And since the house takes such a large cut, the only way for pro players to have positive expected value online is to seek out games with poor players. So even if they couldn't recognize the bots as such, they would see them as tough players and avoid them.

That said, I suppose it would be possible for the bots to become so prevalent that all this sort of opportunity is effectively used up, so the return vs time and risk for a human player is no longer worthwhile. (That already happened long ago for most players, as the initial online poker boom faded and most casual players left.)

On the other hand, all the major platforms have terms prohibiting using bots, so their numbers might be sufficiently limited to prevent that scenario.

It's my understanding the big sites have some pretty sophisticated bot detection systems, so in theory a bot that would be successful at beating online poker couldn't be a huge winner, it'd presumably raise too many red flags. However, if it were a near break-even player, with dozens, if not hundreds, of instances running at any given time, it's going to slowly grind out a substantial figure. You'd also have to take into account that the sites are monitoring things like reaction times to bets and raises, hand range consistency, etc. I'm not a coder, but it seems like it'd be a tremendous undertaking to code a bot that would be a substantial threat to players. Then again, maybe I'm naive about the level of scrutiny the poker sites are employing.

One of the professors I used to work with some years ago was involved in stylometry research on human-computer interactions such as keystrokes and mouse input (for example, to determine if a user who had authenticated successfully earlier is not the same person currently typing based on keystroke cadence and pattern analysis - e.g. if someone sat down at an unlocked workstation and started typing, you could detect it and force them to reauthenticate).

It would probably be possible to figure out the types of detection being performed by the poker sites and use adversarial training methods to train a machine learning solution to mimic human input patterns. Or, more pragmatically, have the bot analyse the state of the game and give orders for a human to perform at their own natural pace.

Poker sites mainly detect bots based on their login times, number of tables, time per action, etc.

A successful bot shouldn't get caught for "playing like a bot" because the moment it's actions are that predictable it would presumably no longer be effective.

But it will get caught for operating like a bot. So, don't run it 24hrs a day. Sites also randomize things to keep bots at bay, even card imagery.

If your performance and success drops whenever they randomize something that gives the bot false inputs, then you might get caught.

Inputting all of the poker events manually would be really tedious I'd imagine.

Of course, if you're winning millions, they can interview you about your poker history and how you got so good.

It sounds like easy money, but probably not.

Just play as you normally would, with the bot advising moves from the laptop next to you.

Right, but the bot needs to know who is in what position what the bets are, who folded, etc. Try inputting all of that information manually to the laptop next to you and you'll quickly get frustrated. Online poker is a fast game with lots of data points.

TensorFlow, PyTorch, Caffe, Keras, MXNet, and OpenCV could copy the game if you split the video input for the player and the bot.

Yes, but see my previous comment.

People have tried it and online poker sites know they've tried it, so they'll randomize images and other data. If you take a dive when the randomizations are triggered and outperform otherwise good luck trying to collect your winnings.

An external camera with Image processor does that

Not to mention, if you get caught, there could be worse consequences than just having your account locked. The site could (and likely would if the scale was significant) sue you for not only all your winnings, but damage to their business. They would likely win (since you're flagrantly breaking their terms of use contract), and bankrupt you.

Edit: In fact, if we're talking worst case, circumventing their anti-bot restrictions would presumably be illegal under the CFAA. So if you're in the US you could even be charged criminally, although I expect in reality that would be less likely.

>You'd also have to take into account that the sites are monitoring things like reaction times to bets and raises, hand range consistency, etc.

You might be surprised by the lengths people go to in order to bypass bot-detection just for ordinary games. All of the things you mentioned are pretty standard. Considering there is serious money on the line here, I am positive that plenty of poker bots will be virtually indistinguishable from professional players, if they aren't already.

The same argument of money being on the line applies to the detection. Poker software is already pretty damn impressive with its tracking. The online casinos actually stand to lose more money than the bot creators could make, so the detection has a greater incentive, and is likely to triumph.

They only lose if there are less plays, surely? I assume they take a cut of all winnings, they're not putting up stakes.

Yes, I'm assuming that if bots work their way into everyday online poker that people will stop using it, so there would be less players.

I guess the real threat isn't a "bot" but something in the way of a program that interprets the data on the screen real-time and whose output instructs the player of the "optimal" play, given the circumstances. How the hell would you deter that as a site operator?

No, I think your earlier example of a swarm of just-above-break-even bots would be much more difficult to combat. Even if they can be detected, the anti-detection countermeasures can evolve, turning it into an arms race. Anything you can model in your bot detection algorithm, the bot-maker can model too.

Reaction times ought to be one of the easiest things to fake. All it would take is a bunch of monitoring of large numbers of games to create a nice model of real player reaction times, which in all likelihood are normally distributed anyway.

Not normally distributed, as negative reaction times are unlikely. You could use log-normal, but I believe that a mixture of exponential and gamma tends to be used by reaction time researchers (search ExpGamma).

negative reaction times are unlikely

Oh, right. I was thinking along the lines of 100m dash, where people often do have negative reaction times (which we penalize as false starts).

In poker we don't have much of an incentive to react instantly to any play.

Pretty sure I've read a long time back on 2p2 that large consistant winners on certain sites have been asked to submit camera footage of their play with a clear view of screens and inputs. So this is probably something that companies like Pokerstars have been dealing with for years already.

It would be pretty easy to hide something signalling you on what to play from cameras.

True, but ultimately if they're unsure they'll just ban you from the platform anyway. Consistent, winning players aren't really where they make their money, and they're free to ban anyone they like. (I realize technically they take a cut from all players, but more money gets sloshed around for them to skim off of if winning players aren't removing it from the system.)

That was what I was thinking, the bot augmenting a human's playing ability rather than playing itself.

> So even if they couldn't recognize the bots as such, they would see them as tough players and avoid them.

The problem would be if i was a pro i would rather run 1000 bots than play myself. Which means the only players left are AI and fish. Once the fishies learn of this fact, they will abandon in drove.

It's all gonna go back to live poker soon.

No, having losing odds never stopped anyone from gambling.

That's simply not true... I don't play casino games because of the losing odds. I play poker because of the winning odds. I guess you meant "having losing odds doesn't stop everyone from gambling".

Even with a magical human test, you couldn't know whether it was human + robot performance.

Just bet on bots playing each other.

So... like Wall Street!

I'm sitting here considering the possibility of making my own bot to play low stakes online poker ($1.50 sit n go). Run it on 6 tables at once and I imagine it would be facing really poor opponents and would have a steady flow of cash.

until your bot gets caught (possibly quickly) and then you're banned from the sites.

Even if it is, it means a new live poker boom which is a very good thing

It must be. It is way too hard to prevent humans from using an AI. Some chess services try to check if you're playing "too perfect", but in poker that's harder to do, and there's way more money on the line.

>> Some chess services try to check if you're playing "too perfect", but in poker that's harder to do, and there's way more money on the line.

Not really. With perfect information you know the correct strict equity plays assuming normal opponents. This doesn't give you the ultimate answer, because a player's reads and inference about another player is definitely an input - especially at the highest level - but it is more than enough to give you a winning/losing player at the small/midstakes.

source: worked for an online poker company that had these tools... and far more available to us

> a player's reads and inference about another player is definitely an input - especially at the highest level

I think player-dependent strategy is more important at lower levels because the players are much further away from what you call "normal opponents", so there's far more opportunity to exploit their mistakes.

>Some chess services try to check if you're playing "too perfect" [...]

That's interesting, could you share an example? Most of my search results are anecdotal Reddit threads about how many people cheat in online chess.

All the major online chess websites have anti-cheat mechanisms. They don't publish details of how they detect cheaters though, and I don't know how good they are.

From what I've read, they work by comparing the player's moves against chess engines, and if the player is picking engine's choice too often in positions where there are multiple roughly equal moves, they get flagged.

I always found weird that someone would want to cheat in a game like online chess. I mean, what's the point? Does anyone have insight on what's going on in the head of cheaters?

A few reasons come to mind. One is simply that if you have any metrics (ranking, win/loss ratio, greater site access..) it's going to feel nice to see them improve. Another is that losing at anything can be ego-hurting (similar reason good players sometimes sandbag with new accounts / lower ranks they can't possibly lose to, they need to 'win' more). Or reverse sandbagging/trolling with a bot might be amusing. Another is the cheater may justify it as a self-teaching game, and might not always play the strongest move but see if their move is even in consideration or try to improve ability to see the better moves by having them always pointed out -- but why not just play the bot, or save that for post-game analysis? I like to run my go games through gnugo's annotated analysis at the end (as I'm very weak I assume even the weak gnugo can teach me things), it'd be too troublesome to use it in a live game.

Other players justify cheating by convincing themselves that everyone else is cheating.

it's where the enjoyment comes from. cheaters don't enjoy the game as much as they seeing their ELO/MMR go up or in the worst case they're psychopaths who just want to mess with other people's heads.

People enjoy the the feeling of having power over others.

Even so most people don't bother with standard games online since its way too easy to cheat by mirroring the game and basically undetectable if they are good enough to not play lines that look like "computerish" moves.

>> Computers are better at maths than humans.

OP discussed it but while this is true, it is not necessarily true or straightforward when it comes to games with hidden information like poker. This is more of a game theoretical problem (Economics) than it is a purely mathematical one, which had less support in the AI/ML community, hence the delay.

The lower CPU/GPU/resource use supports that fact as does your intuition. Breaking poker required a lot of manual work and model design over brute force algorithms and reinforcement learning.

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