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[–] SaneGoatiSwear 7 points 6 points (+13|-7) ago 

notice i stopped calling out bots?

because the more they learn about what we use to call them out

the more they learn.

fuck that, fuck ai.

fuck the whole fucking thing

each goat has to surmise for themselves whether whom they're talking to is a bot or not.

and they ARE still here.

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[–] OneTrueCube 0 points 5 points (+5|-0) ago  (edited ago)

Are you a robot?

Edit: holy shit this would actually be the biggest plot twist of all time, if Sane was a elaborate AI let loose on Voat

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[–] creep 0 points 1 points (+1|-0) ago 

It would explain a lot.

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[–] Zaqwert 0 points 4 points (+4|-0) ago  (edited ago)

As more players are added the complexity of playing goes way up though. For example if playing a 6 handed match trying to evaluate the optimal play becomes way harder when you have 1-5 opponents, each opponent having their own style/history, and your position relative to them in the hand varies significantly, etc.

Heads up is much more static and therefore much simpler to analyze. One opponent, every hand. One of two possible positions, every hand, etc.

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[–] rwbj [S] 1 points -1 points (+0|-1) ago 

I don't think so. A big difference is that as you add more players, absolute hand value becomes far more important. Imagine a theoretical 20 handed game. Correct strategy would be pretty much nut peddling. The 'nuts' in poker being the best possible hand. AA preflop, 99 on a 972 flop (first 3 cards), etc. Card removal also makes it a lot easier to nail down ranges. For instance if at a 9 handed table it folds to the small blind then not only he but also the big blind are much more likely than usual to have good hands due to the implicit card removal of everybody folding. So this reduces the relevance of 'stealing.' As you reduce the number of players absolute hand value becomes less important, ranges and realizing equity becomes far more important. These are all very complex concepts and I think this is the reason that winrates in poker tend to be inversely proportional to the number of players. So a great winrate at a 9-handed game is going to be a small fraction of a great winrate heads up.

The AI is also not playing exploitatively in the sense of exploiting the specific players. It's playing the same way against everybody. So in this event all 4 players, though working together, certainly have their own unique styles and strengths yet the AI crushed them all without individual adjustment.

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[–] Zaqwert 0 points 0 points (+0|-0) ago  (edited ago)

While it's true that in a larger game the hand value becomes more important than in heads up, the other aspects I mentioned lead to a more overall complex game for an AI to model.

You could easily build an AI that wins at a full game against average players, hell they already exist I'm sure, by playing a very tight ABC style, however building one that would always crush the game, even against good opponents, is way more of a challenge.

In other words building an AI that plays "perfectly" heads up is far easier than building one that plays "perfectly" in a full game, however building an AI that does extremely well in full games is pretty low hanging fruit I'd imagine.

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[–] drakesdoom 0 points 2 points (+2|-0) ago 

Would get thrown out of a casino before it sat down. NO CARD COUNTING HERE.

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[–] derram 0 points 2 points (+2|-0) ago 

https://archive.is/ddzu2 :

We are professional poker players currently battling the world's strongest poker AI live on Twitch in an epic man-machine competition (The AI is winning). Ask us, or the developers, anything! : IAmA

This has been an automated message.

[–] [deleted] 0 points 1 points (+1|-0) ago 

[Deleted]

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[–] rwbj [S] 0 points 1 points (+1|-0) ago 

Well you're really just off here. This is the difference between an expert system and reinforcement learning system. Expert systems are what you're describing that effectively navigate a hardcoded logic - 'if I have AA then raise, if I have 93o then fold, etc.' Reinforcement and deep learning systems instead learn by examining their results in different scenarios and specifically rely on new information to improve. Like mentioned each night the AI would do its thing and learn from the hands played during the day. This does not mean the programmers changing the AI, but the AI changing itself.

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[–] european 0 points 0 points (+0|-0) ago 

There are already bots that do well online, but nothing like this.

With something this good and the amount of money at stake online , I'd suspect that someone is using this or something similar online right now.

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[–] Saufsoldat 4 points -2 points (+2|-4) ago 

And this is surprising why? Poker is a far simpler game than go or even chess and AI has beaten us in both.

Good on the researchers, but they're a few years late with this.

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[–] european 0 points 5 points (+5|-0) ago 

poker is a game of incomplete information though.

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[–] Saufsoldat 0 points 0 points (+0|-0) ago 

It's also a game of probability, which computers excell at.

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[–] Traveler 1 points -1 points (+0|-1) ago 

Shut the fuck up already

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[–] Saufsoldat 0 points 0 points (+0|-0) ago 

What crawled up your ass and died?

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[–] rwbj [S] 1 points -1 points (+0|-1) ago 

I think this is a far greater accomplishment than chess. The reason is that poker is largely a 'big picture' game. Chess is a very tactical game where one move can be, and often is, the difference between victory and defeat. Even at the highest level you'll see players like Magnus Carlsen, current world champion and arguably the strongest player ever, missing winning (and losing) moves. For computers to crush humans at chess it's not necessary for them to play incredibly strong overall, but simply to never play anything less than very strong.

Poker on the other hand is the exact opposite. The result of any given hand is pretty much irrelevant. Like if you ever see something on television with commentators acting like JJ vs 99 on a board of J 9 2 is interesting. It's not. If both players play optimally 99 should lose his money there every single time and in the longrun the value in that spot is $0 since you'll end up being on the happy end and being on the sad end with the same frequency.

What decides the results in the longrun in poker is the accumulation of very tiny edges, particularly in small pots. For instance at a game with 6 players a player raises from early position. A player in the small blind calls with 67 of diamonds and then folds when he misses the board. That 67 player is spewing money against good play, but without a decent understanding of poker it's not so easy to understand why. In heads up play this nuance becomes even more pronounced as adaption and hand ranges become even more complex. Now give each player 200 big blind stacks and you ramp up the complexity exponentially.

And this AI was not an expert system. An expert system is basically a rule driven AI that comes down to "If this and this is true, then do that. If this and this and this is true then do this..." Even if it was, this would still be a big accomplishment but the fact it wasn't makes this all the more incredible. This was a reinforcement learning AI that 'taught itself' how to play high level poker by playing trillions of hands against itself and then adapted to human play with brutal efficiency. This is a decent proof of concept for more or less any sort of incomplete information activity such as, for instance, human negotiations.

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[–] CrowTRobot 0 points 0 points (+0|-0) ago 

instance at a game with 6 players a player raises from early position. A player in the small blind calls with 67 of diamonds and then folds when he misses the board. That 67 player is spewing money against good play

This is oversimplified. Determining the quality of that play needs to include the sizes of stacks, player images, the size of the raise...