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You talk about brute force, but again that's just nonsense. The only reason why this matters is because of computing power and as I pointed out in the last published article posted that was misrepresented, the Researchers tried to figure out ways to reduce this. That doesn't really matter though because quantum computing will throw that problem out of the window.
First, the AI’s algorithms computed a strategy before the tournament by running for 15 million processor-core hours on a new supercomputer called Bridges.
Second, the AI would perform “end-game solving” during each hand to precisely calculate how much it could afford to risk in the third and fourth betting rounds (the “turn” and “river” rounds in poker parlance). Sandholm credits the end-game solver algorithms as contributing the most to the AI victory. The poker pros noticed Libratus taking longer to compute during these rounds and realized that the AI was especially dangerous in the final rounds, but their “bet big early” counter strategy was ineffective.
Third, Libratus ran background computations during each night of the tournament so that it could fix holes in its overall strategy. That meant Libratus was steadily improving its overall level of play and minimizing the ways that its human opponents could exploit its mistakes. It even prioritized fixes based on whether or not its human opponents had noticed and exploited those holes. By comparison, the human poker pros were able to consistently exploit strategic holes in the 2015 tournament against the predecessor AI called Claudico.
however, we developed a technique for computing the joint distributions that requires just O(n) strategy table lookups.
A primitive programming style in which the programmer relies on the computer's processing power instead of using his own intelligence to simplify the problem, often ignoring problems of scale and applying naive methods suited to small problems directly to large ones.
Even more important, the victory demonstrates how AI has likely surpassed the best humans at doing strategic reasoning in “imperfect information” games such as poker.
The system is learning and it's not Poker specific. As I mentioned earlier, this is one of the goals of A.I. To make intelligent systems that can learn across all areas. It came up with it's own strategy and the only input was the rules of Poker. The Programmers didn't tell it what strategy to use or which strategy to learn in a game where they have to bluff because it has imperfect information. There goes your brute force. How can it be simply calculating information from it's environment when it doesn't have all of the information? It's not even algorithms that are poker specific.
Even more important, the victory demonstrates how AI has likely surpassed the best humans at doing strategic reasoning in “imperfect information” games such as poker. The no-limit Texas Hold’em version of poker is a good example of an imperfect information game because players must deal with the uncertainty of two hidden cards and unrestricted bet sizes. An AI that performs well at no-limit Texas Hold’em could also potentially tackle real-world problems with similar levels of uncertainty.
“The algorithms we used are not poker specific,” Sandholm explains. “They take as input the rules of the game and output strategy.”
In other words, the Libratus algorithms can take the “rules” of any imperfect-information game or scenario and then come up with its own strategy. For example, the Carnegie Mellon team hopes its AI could design drugs to counter viruses that evolve resistance to certain treatments, or perform automated business negotiations. It could also power applications in cybersecurity, military robotic systems, or finance.
There is some good news for anyone who enjoys playing—and winning—at poker. Libratus still required serious supercomputer hardware to perform its calculations and improve its play each night, said Noam Brown, a Ph.D. student in computer science at Carnegie Mellon University who worked with Sandholm on Libratus. Brown reassured the Twitch chat that invincible poker-playing bots probably would not be flooding online poker play anytime soon.
originally posted by: Aedaeum
I want to shout out to Azadan and Protector for their insight on AI; it was very illuminating. Azadan, I was wondering if I might be able to pick your brain in PM? I have a project I'm working on that I'd love to have your advice on, though I'm afraid you might not be coming back to this thread haha for obvious reasons.