Poker


World Series of Poker Tournaments Kick off in Las Vegas

U.S. News

"In regular poker, to force betting, each person puts in an ante," Palansky said. "We've changed some tournaments where one person essentially pays everyone's ante at once. So, when you are in a particular spot at the table, you pay everyone's ante and the rest of the time you don't pay any ante at all. If the ante is a chip value of 100, that person may put in 900 for all nine players.


To drive AI forward, teach computers to play old-school text adventure games

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Games have long been used as test beds and benchmarks for artificial intelligence, and there has been no shortage of achievements in recent months. Google DeepMind's AlphaGo and poker bot Libratus from Carnegie Mellon University have both beaten human experts at games that have traditionally been hard for AI – some 20 years after IBM's DeepBlue achieved the same feat in chess. Games like these have the attraction of clearly defined rules; they are relatively simple and cheap for AI researchers to work with, and they provide a variety of cognitive challenges at any desired level of difficulty. By inventing algorithms that play them well, researchers hope to gain insights into the mechanisms needed to function autonomously. With the arrival of the latest techniques in AI and machine learning, attention is now shifting to visually detailed computer games – including the 3D shooter Doom, various 2D Atari games such as Pong and Space Invaders, and the real-time strategy game StarCraft.


Teaching computers to play Doom is a blind alley for AI – here's an alternative

The Independent

Games have long been used as testbeds and benchmarks for artificial intelligence, and there has been no shortage of achievements in recent months. Google DeepMind's AlphaGo and poker bot Libratus from Carnegie Mellon University have both beaten human experts at games that have traditionally been hard for AI – some 20 years after IBM's DeepBlue achieved the same feat in chess. Games like these have the attraction of clearly defined rules; they are relatively simple and cheap for AI researchers to work with, and they provide a variety of cognitive challenges at any desired level of difficulty. By inventing algorithms that play them well, researchers hope to gain insights into the mechanisms needed to function autonomously. With the arrival of the latest techniques in AI and machine learning, attention is now shifting to visually detailed computer games – including the 3D shooter Doom, various 2D Atari games such as Pong and Space Invaders, and the real-time strategy game StarCraft.


How poker and other games help artificial intelligence evolve

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Michael Bowling has always loved games. When he was growing up in Ohio, his parents were avid card players, dealing out hands of everything from euchre to gin rummy. Meanwhile, he and his friends would tear up board games lying around the family home and combine the pieces to make their own games, with new challenges and new markers for victory. Bowling has come far from his days of playing with colourful cards and plastic dice. He has three degrees in computing science and is now a professor at the University of Alberta.


APNewsBreak: 3-State Online Poker Pool to Debut May 1

U.S. News

"This has been a huge collaborative effort from all involved and it is important to thank the elected leadership and regulatory authorities in Delaware, Nevada and New Jersey for their dedication and diligence to help move online poker forward," said Bill Rini, WSOP.com's head of online poker. "Everyone has had the end user in mind throughout this process, and as a result, we believe the United States, for the first time in a regulated environment, will have a large-scale multi-state offering that will propel the industry forward as soon as next month."


Poker AI Revolution [Infographic] Techno FAQ

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AI has a long history of defeating human players in games. IBM's "Deep Blue" developed by Carnegie Mellon University beat chess world champion Garry Kasparov in their re-match in 1997. Google AlphaGo AI won the game "Go" by defeating leading Go player Lee Sedol. IBM supercomputer Watson beat two "Jeopardy" champions at their own game in 2011. But, did you know that AI recently conquered the very human game of Poker?


AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games

AAAI Conferences

Evaluating agent performance when outcomes are stochastic and agents use randomized strategies can be challenging when there is limited data available. The variance of sampled outcomes may make the simple approach of Monte Carlo sampling inadequate. This is the case for agents playing heads-up no-limit Texas hold'em poker, whereman-machine competitions typically involve multiple days of consistent play by multiple players, but still can (and sometimes did) result in statistically insignificant conclusions. In this paper, we introduce AIVAT, a low variance, provably unbiased value assessment tool that exploits an arbitrary heuristic estimate of state value, as well as the explicit strategy of a subset of the agents. Unlike existing techniques which reduce the variance from chance events, or only consider game ending actions, AIVAT reduces the variance both from choices by nature and by players with a known strategy. The resulting estimator produces results that significantly outperform previous state of the art techniques. It was able to reduce the standard deviation of a Texas hold'em poker man-machine match by 85\% and consequently requires 44 times fewer games to draw the same statistical conclusion. AIVAT enabled the first statistically significant AI victory against professional poker players in no-limit hold'em.Furthermore, the technique was powerful enough to produce statistically significant results versus individual players, not just an aggregate pool of the players. We also used AIVAT to analyze a short series of AI vs human poker tournaments,producing statistical significant results with as few as 28 matches.


The Annual Computer Poker Competition

AI Magazine

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.


Revealed: How Libratus bot felted poker pros – and now it has cyber-security in its sights

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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.