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Libratus poker video





This is a high-level overview of the system, of course, and the paper goes into some more detail.
Libratus burned through approximately 19 million core hours of computing throughout the tournament.
Now, a paper published in Science reveals how Libratus was programmed.
Our game-theoretic approach features application independent techniques: an algorithm for computing a blueprint for the overall strategy, an algorithm that fleshes out the details of the strategy anti aging body loton sisley for subgames that are reached during play, and a self-improver algorithm that fixes potential weaknesses that opponents have.
The software's victory over humans sparked a lot of headlines as it adventure week 2018 bonus xp 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 opponents cards.The code, however, will not be released publicly as the technology behind Libratus has been exclusively licensed to Strategic Machine, a startup founded by Sandholm in March this year.PDF won best paper at nips 2017.Meet the bot, Libratus.It would analyze the frequency of its opponents' bet sizes, and update itself overnight, improving throughout the competition.The first algorithm was briefly discussed after the competition as counterfactual regret minimization.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.Sponsored: Five steps to dealing with the insider threat.Dong Kim, one of Libratus opponents, previously said the competition was extremely tough as the AI keeps getting better.By watching how its human rivals played, Libratus fleshed out the relatively simple "blueprint" decision tree with extra nodes to help it win hands against those opponents.

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Sandholm said it could be deployed to help organizations thwart hackers exploiting zero-day vulnerabilities, where bugs in software are unknown to the folks trying to defend against such attacks.
The machine crushed its meatbag opponents.7 big blinds per game, drawing in 1,776,250 in prize money.
Treating those hands as identical reduces the complexity of the game and thus makes it computationally easier.This algorithm was dubbed "nested subgame solving.".It could achieve, at maximum,.35 pflops or more than a quadrillion floating-point math calculations per second.In principle, one could conduct all such computations in advance, but the game tree is way too large for that to be feasible, the paper stated.Libratus pushed the envelope when it comes to poker strategy.




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