Posted: Mar 03, 2017 4:32 pm
by tuco
AI shoves all in: DeepStack, Libratus poker bots battle Texas Hold 'em pros heads up

AI poker intuition
A game between two players betting any number of chips produces 10160 possible situations – a number too large for a computer to handle. To skirt around the problem, DeepStack “squeezes” it down to 1014 abstract situations that are learned by playing against itself.

Like DeepMind’s AlphaGo, DeepStack picks the best move to take by drawing on a bank of possible moves by calculating what types of scenarios are more likely, something the researchers compare to intuition: “A gut feeling of the value of holding any possible private cards in any possible poker situation.”

The programme’s “intuition” has to be trained using two neural networks. One learns to estimate the counterfactual – or “what-if” values after the first three public cards are dealt, and the other neural network recalculates the values after the fourth public card is dealt.

Simplifying the number of situations means the decision tree computed by DeepStack is effectively pruned, and it’s easier to approximate the Nash equilibrium – a solution in game theory which states that no player has an incentive to change his or her strategy – continuously, after each round.

Since it doesn’t have an overarching strategy decided before the game, it doesn’t need to keep tabs on all 1014 abstract situations – it can solve the decision tree in under five seconds.

“The DeepStack algorithm is composed of three ingredients: a sound local strategy computation for the current public state, depth-limited lookahead using a learned value function over arbitrary poker situations, and a restricted set of lookahead actions,” the paper said.


https://www.theregister.co.uk/2017/01/14/deepstack/

DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker - https://arxiv.org/abs/1701.01724