Recently, an artificial intelligence from Carnegie Mellon University managed to defeat four professional poker players playing Texas Holdem.
Now the creators of this AI have just confirmed that Libratus has a superhuman ability to win this game.
He did it with more decision points than atoms have in the universe.
Therefore, they apply to a large number of imperfect information sets.
An example of these abstractions in poker is to group similar hands and treat them identically.
Intuitively, theres little difference between a King-high ladder and a Queen-high colour, Brown said.
During the January competition, Libratus made this calculation using the Bridges computer from the Pittsburgh Supercomputing Center.
Sandholm and Brown call this nested sub-game solution.
The third module is designed to improve the strategy of the plan as the game progresses.
Typically, Sandholm said, robots use machine learning to find mistakes in the opponents strategy and exploit them.
Instead, Libratuss self-execution module analyzes the size of opponents bets to detect potential holes in the strategy itself.
Then, Libratus adds these missing decision branches, calculates strategies for them and adds them to the plan.
In addition to beating human professionals, Libratus was evaluated against the best artificial intelligence in poker.
The machines see a game as a tree.
Simplifying, two branches come out of each node, which are the possible decisions or paths to take.
For each of these branches fruit sprout, which are the possible reactions of the opponent.
According to where the fruit has come from, so will two other branches emerge.
Foliage and fruits compete for one goal: to reach the sunlight.
Obviously, not all the branches are so leafy, nor all the fruits so compromising for them.
But that takes time.
For this reason, some branches can be clipped with their fruits, leaving it narrower.
Neural networks are like experienced gardeners.
So, what do you think about this?
Simply share your views and thoughts in the comment section below.
