CMU Researchers Reveal How Their AI Beat The World's Top Poker Players (triblive.com)
2017 began with an AI named "Libratus" defeating four of the world's best poker players. Now the AI's creators reveal how exactly they did it. An anonymous reader quotes the Pittsburgh Tribune-Review:
First, the AI made the game easier to understand. There are 10**161 potential outcomes in the game of poker -- that's a one followed by 161 zeros, potential outcomes in a game of poker. Libratus grouped similar hands, like a King-high flush and a Queen-high flush, and similar bet sizes to cut down that number. Libratus then created a detailed strategy for how it would play the early rounds of the game and a less-refined strategy for the final rounds. As the game nears the end, Libratus refined the second strategy based on how the game had gone.
A third strategy was at work as well. In real-time, Libratus created another model based on how its play stacked up against the play of the humans. If the humans did something unexpected to Libratus, the AI accounted for it and built it into the strategy. Instead of trying to exploit weaknesses in the play of the human, Libratus focused on improving its play.
The AI was created by a computer science professor at Carnegie Mellon University and his Ph.D. student, who argue in a new paper that "The techniques that we developed are largely domain independent and can thus be applied to other strategic imperfect-information interactions, including non-recreational applications."
"Due to the ubiquity of hidden information in real-world strategic interactions, we believe the paradigm introduced in Libratus will be critical to the future growth and widespread application of AI."
A third strategy was at work as well. In real-time, Libratus created another model based on how its play stacked up against the play of the humans. If the humans did something unexpected to Libratus, the AI accounted for it and built it into the strategy. Instead of trying to exploit weaknesses in the play of the human, Libratus focused on improving its play.
The AI was created by a computer science professor at Carnegie Mellon University and his Ph.D. student, who argue in a new paper that "The techniques that we developed are largely domain independent and can thus be applied to other strategic imperfect-information interactions, including non-recreational applications."
"Due to the ubiquity of hidden information in real-world strategic interactions, we believe the paradigm introduced in Libratus will be critical to the future growth and widespread application of AI."
It was one thing when bots could beat up on donkeys, but when even the best human players can't win it means only bots will be left standing. That doesn't mean humans are totally out of the loop, someone still has to be standing by to talk to the admin when questioned about their human status -- for now. That too will probably fall before long.
The micro-stakes tables will probably remain largely human because there's very little to lose (or gain) down there, but for high-stakes games this signals a rapidly approaching end.
How is the Riemann zeta function like Trump rallies? Both have an endless number of trivial zeros.
It's way harder if you know you may end sleeping in your car for a couple of years if you lose.
By counting cards. The bouncers will have it thrown out in a minute.
sed -e 's/Chuck Norris/Rajnikant/g' joke > fact
It kind of defeats the point of AI if you preload it with all kinds of statistics a human wouldn't have access to while playing a game. The point of AI is to make a computer think and learn like a human, not to prove that a computer can beat a human. We already know computers are better at calculations than humans.
Laws are rules for the court, but merely a bottom bar to hit for life. Think beyond laws in your actions always.
I followed this as it was happening. This is NOT about bots being able to beat human players. It's about bots being able to beat human players in the simplest possible space that doesn't mimic 99% of actual poker play.
It was only heads-up with 1 human a time, not vs. a table. After every round the money was reset so it never had to play from low amount of chips, or have to try to bully with it's chip advantage. The amount of chips vs. the big blind was a very large stack in the first place even before it reset every hand, so the blinds were statistically little more than noise in the amount that was going back and forth.
Don't get me wrong, this is really interesting and great strides. But this is far from a bot being able to play at a full table and having to deal with a few bad hands taking it out of the place where it's betting is suited for. (If you have less of a stack, you have less of an upside so draw hands aren't worth as much.) Or to have someone with a larger stack push it beyond it's acceptable betting and make it fold because it can.
LITTLE GIRL: But which cookie will you eat FIRST? C. MONSTER: Me think you have misconception of cookie-eating process.