The current most popular variant of poker, played in casinos and seen on television, is no-limit Texas hold'em. This game and a smaller variant, limit Texas hold'em, have been used as a testbed for artificial intelligence research since 1997. Since 2006, the Annual Computer Poker Competition has allowed researchers, programmers, and poker players to play their poker programs against each other, allowing us to find out which artificial intelligence techniques work best in practice. The competition has resulted in significant advances in fields such as computational game theory, and resulted in algorithms that can find optimal strategies for games six orders of magnitude larger than was possible using earlier techniques.
Now entering its eighth year, the Annual Computer Poker Competition (ACPC) is the premier event within the field of computer poker. With both academic and nonacademic competitors from around the world, the competition provides an open and international venue for benchmarking computer poker agents. We describe the competition's origins and evolution, current events, and winning techniques The competition has been held annually since 2006, open to all competitors, in conjunction with top-tier artificial intelligence conferences (AAAI and IJCAI). In 2006 the competition began with only 5 competitors. Since then, the total number of competitors has increased.
The blueprints for Libratus – the poker AI bot that crushed professional players in a Texas hold'em tournament earlier this year – were published on Monday in a research paper. The software's victory over humans sparked a lot of headlines as it demonstrated a computer mastering an imperfect information game. Unlike chess or Go where players can see all the board pieces at all times, poker players have to come up with a strategy based more on probabilities since they do not know their opponent's cards. Libratus emerged as the clear victor after playing more than 120,000 hands in a heads-up no-limit Texas hold'em poker tournament back in February. The machine crushed its meatbag opponents by 14.7 big blinds per game, drawing in $1,776,250 in prize money.
In this tutorial, you will learn step-by-step how to implement a poker bot in Python. First, we need an engine in which we can simulate our poker bot. It also has a GUI available which can graphically display a game. Both the engine and the GUI have excellent tutorials on their GitHub pages in how to use them. The choice for the engine (and/or the GUI) is arbitrary and can be replaced by any engine (and/or GUI) you like.
The Pittsburgh Supercomputing Center received five @HPCwire awards, including one for poker AI'Libratus' The Pittsburgh Supercomputing Center (PSC) received not one, but five HPCwire awards at the 2017 International Conference for High-Performance Computing (HPC), Networking, Storage and Analysis (SC17) on Sunday, Nov. 12. One of the three Readers' Choice Awards that PSC received was for Best Use of AI: CMU School of Computer Science "Libratus" AI on PSC's "Bridges" wins Brains vs. AI competition. HPCwire represents the leading trade publication in the supercomputing community and their annual Readers' and Editors' Choice Awards, given out at the start of the annual supercomputing conference, are well respected in that community. The awards are determined based on a nomination and voting process among the HPCwire community as well as selections from the publication's editors. In addition to Best Use of AI, PSC received two more Readers' Choice Awards -- Outstanding Leadership in HPC (Nick Nystrom, Interim Director, PSC) and Best Use of HPC in Energy (PSC with Texas A&M uses OpenFOAM on PSC Bridges & Texas Advanced Computing Center's Stampede to better understand coolant & heat transfer in high-temperature-jet reactors).
Ever since the inception of Artificial Intelligence, humans have been in a constant battle with the modern thinking-machines. AI has touched many industries, by showing outstanding results and even outperforming humans. As statistics show, 62% of millennials aged 17-24 and 35% of people over 55 trust the super abilities and the future of AI. It is also interesting that 71% of people over 50 believe that intelligent virtual assistants will simplify their lives in the future. Meanwhile, the history of the Brains vs AI battle contains many examples of where one defeats the other.
While such a scenario remains unlikely in the near future, many believe that at least the first part – AI surpassing the human brain and mind to reach a level of artificial superintelligence (ASI) – will most likely happen some time in the next 30 years, according to Jeff Nesbit in U.S. News & World Report. When asked which of Libratus' strategies he can employ in his own game, Kim explained that the bot's mixed strategy made it difficult to play against. In a PokerNews article by Andrew Robl in 2016, he notes six characteristics that make for a successful player, five of which can be ascribed to a bot like Libratus: experience, intelligence, desire and willingness to learn (minus the desire part), ability to control emotions and having a "sick" amount of gamble. Meanwhile, Libratus kept chugging along, adapting its strategy based on experience, consistently making optimal plays.
That's why, when confronted with the video above, I decided to "drill down" (as they say in the boardroom) into what's probably the most spectacular of the examples: the poker-playing program from Carnegie Mellon University that bested professionals in tournament play. It briefly explained what the program, called Libratus, had accomplished, which was factual enough. The question is important because "strategic reasoning" implies the ability to creatively adapt to constantly changing circumstances. However, the fact that Libratus can win poker tournaments is no indication that AI is any closer to being able to cope with complex, open-ended situations--at least not without humans to keep tweaking the program to match the changing nature of the real world.
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It's there you'll find the professors who solved the game of checkers, beat a top human player in the game of Go and used cutting-edge artificial intelligence to outsmart a handful of professional poker players for the very first time. He's a pioneer in a branch of artificial intelligence research known as reinforcement learning -- the computer science equivalent of treat-training a dog, except in this case the dog is an algorithm that's been incentivized to behave in a certain way. U of A computing science professors and artificial intelligence researchers (left to right) Richard Sutton, Michael Bowling and Patrick Pilarski are working with Google's DeepMind to open the AI company's first research lab outside the U.K., in Edmonton. Last week, Google's AI subsidiary DeepMind announced it was opening its first international office in Edmonton, where Sutton -- alongside professors Michael Bowling and Patrick Pilarski -- will work part-time.
Over the past three weeks, an AI poker bot called Libratus has played thousands of games of heads-up, no-limit Texas hold'em against a cadre of top professional players at Rivers Casino in Pittsburgh. Poker requires reasoning and intelligence that has proven difficult for machines to imitate. Artificial intelligence has never beaten top players at a game so lacking in information as no-limit Texas hold'em. Still, given the progress machine learning is currently making, and the fact that other AI poker bots are also being developed, that seemingly impossible challenge may not remain impossible for long.