In the past when someone wanted to play poker online, they had to find a group of like-minded individuals who were on a similar quest. Today the process is much easier thanks to online casinos and even more so since AI entered the scene.
When machines are given a large quantity of data, they may search for patterns in that data to learn how to solve issues. The difficulty is that they rely on mathematical answers to problems. Consider the game of chess. Chess is a highly conclusive game. Apart from the initial few moves, there is always the best play in chess, which is why Chess AIs can annihilate even the finest grandmasters. In the instance of chess, machines will assess the outcomes of each move and select the one that is most likely to win.
Why Poker is different?
There is a psychological factor to Texas Hold’Em (albeit there is still a mathematical part), which is difficult for robots to master, however, the addition of bluffing complicates matters. In Chess, the best move can be determined based on the current actions and the opponent’s likely moves, but Texas Hold’Em necessitates the use of intuition (even if logic says no). Players can bluff, overbet, or use other tactics that seem to defy logic.
Every player plays differently
So, how do you modify the AI to adapt to each player’s strategy? Because knowing how your competitor plays is essential to becoming a solid poker player. Some players are “tight,” meaning they will only play a hand if their original two-card hand is statistically above-average and therefore will only call if they have a mighty hand. Other players are “loose” players who will play any hand and frequently call only with good hands. The goal is to divide the game into smaller sections and adapt your approach as the game goes. Thus, the AI may employ machine learning to identify and exploit holes in its opponent’s tactics, and now even win games.
There’s also the issue of not knowing your opponent’s hand. In Chess, both players are always aware of the exact status of the board. Because there are two concealed cards in Poker, no player ever knows the actual condition. This makes predicting the game’s eventual conclusion difficult. It’s also difficult to account for luck because Poker is genuinely a game of chance. You can start with the most incredible hand (a pair of Aces), but you’d be shaking if the four out of the five communal cards were all of the same suit, as a flush and the game could be in the hands of another player.
What have researchers done?
While there is no particular technique to account for this (artificial intelligence playing Poker will always be an approximation), academics attempt to solve the issue by developing a game and abstraction where comparable hands are grouped. This makes it significantly easier for the AI to assess the vast array of possible hands that the other players may have.
The current state of Poker
Artificial intelligence is already capable of defeating professional poker players. In terms of strategy, it is also becoming increasingly customary to consult with artificial intelligence. More individuals than ever before can employ artificial intelligence to better their methods. While traditional poker players would learn by losing money, modern players learn by playing against machines. This is because scientists have created artificial intelligence to assist professional poker players in learning more about optimum poker strategy, allowing them to become better players and win more money in high-stakes games.
This has had a significant influence on the poker industry. People are now more likely to try risk strategies and take chances they otherwise would avoid because of the fear of failing.
Do people use AI to improve at Poker?
A professional poker player, Seth Davis, was competing in the World Series of Poker when he concluded a hand with no valued cards and few alternatives. Davis opted to bluff and claimed that he was “all-in” for the round, putting his $250,000 tournament registration fee (not to mention his dignity) on the line.
Davis was relieved when his opponent folded, and he won the hand. That night, he evaluated the hand with PioSOLVER, an AI-based technology that has fundamentally changed how Poker is played in recent years. Within a few seconds of entering the hand’s facts, the computer informed Davis that he had played the hand quite precisely and that his bluff was the correct move.
Thanks to AI, this luck-based game is transforming into a more calculated game with a strategy and a clear improvement method. What does this improvement in AI mean in the long run? Considering that a machine can outplay people in a game of chance and uncertainty, how long will it be before AI makes accurate decisions that are bigger than a handful of cards?