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Meanwhile, Libratus kept chugging along, adapting its strategy based on experience, consistently making optimal plays. Online Casinos in Malaysia As far as real-world implications, which are the ultimate goal of research on AI in poker, the success of Libratus — in particular its ability to bluff — is momentous. Man Proves Greater Than Machine: In the past decade, much of that research has shifted to creating poker-playing AIs. In the last two decades, AIs have defeated humans in a variety of games including chess, Go, and Jeopardy. Check out our online poker section for details on all the online poker rooms around.

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Have you read the latest Poker news? It is just that in their case their experience comes with playing more than 10 million randomly generated Poker game situations. And one thing is different between us here. Machines learn fast, super-fast! So, it is natural that the Poker AI machines have managed to gather and analyze enough data from their playing experiences, in order to beat the money out of your pockets, humans.

And, even if Poker is considered a game of uncertain information, Poker bots know how to recalculate their algorithms as soon as new information is found. You better be aware now, that the introduction of Poker AI is a real revolution in the gaming arena. Just like the recent major win of Libratus Poker AI proves, AI are coming after you and there is not a thing you can do about it.

Actually, to answer a single question remains: Are humans done with playing Poker? Probably not, but the application of poker is proving to be a great tool for developing advanced artificial intelligence. While AI research has been done in a variety of fields, applying it to strategy games has been one of the most prevalent.

In the last two decades, AIs have defeated humans in a variety of games including chess, Go, and Jeopardy. In the past decade, much of that research has shifted to creating poker-playing AIs. Noam Brown , Ph.

In , Claudico was defeated by a team of four players. Polk recently told PokerNews that Claudico "used a very complex strategy, consisting of many small and large bets" and the AI had some leaks. The new and improved iteration, Libratus, faced off against four top pros in January And we were not ready for that, so it was overall really, really tough. The reason for that? The AI analyzed its own play each night, correcting mistakes and using different strategies the following day.

It also randomizes its actions, making it hard for opponents to decipher whether it is bluffing or not. Most amazingly, Libratus is not just a poker AI, but can be applied to any imperfect information system, with countless potential applications.

Really what it does is it runs into a situation repeatedly and it notices that even if it doesn't have a very strong hand that it can still make more money by betting. Libratus' co-creator Tuomas Sandholm assessed the implications of the bot's victory in a release from Carnegie Mellon. Polk echoed that sentiment when he told PokerNews , the leaks he noticed in Claudico were fixed in Libratus. As far as real-world implications, which are the ultimate goal of research on AI in poker, the success of Libratus — in particular its ability to bluff — is momentous.

Frank Pfenning , head of the Computer Science department at CMU, said incorporating bluffing was a key concept, as it couldn't win without the ability. That's just the beginning. What makes AIs like Libratus so good? While having some emotion while playing poker is not inherently bad — and may even be beneficial in some cases — one major characteristic that separates successful professionals from break-even or losing amateurs in the game is the ability to imitate robots, in a sense.

In a PokerNews article by Andrew Robl in , he notes six characteristics that make for a successful player, five of which can be ascribed to a bot like Libratus: The sixth one is all humans, though — social and networking skills. The bots are lousy at that — for now. The AIs have a clear advantage over humans in terms of emotion, including tilt and fatigue factors. And it is a better player because of it. One comment from Kim after facing off against Libratus highlighted this key difference between bots and humans:.

It was more the constant losing. Team morale was pretty down. Meanwhile, Libratus kept chugging along, adapting its strategy based on experience, consistently making optimal plays.

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