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The main problem with artificial intelligence is not about winning Xgtiger Casino poker chess, a game of Go, or solving a Rubik’s cube. In fact, while all these games have a huge number of plays, they are still very clear in terms of options. When it comes to playing poker, everything changes quickly and this is clearly visible when trying to program a bot that ‘thinks’.
The Tricky Part
So, what is a poker bot? A poker bot is a program designed to play poker against humans and other programs. The invention of such a bot would seem to change the very essence of online poker and turn the online poker world into a battleground between humans and bots. However, not everything is so easy. The main problem is turning meaningful data into an effective and useful game strategy. In general, finding and obtaining a specific set of rules for the poker bot can help it achieve optimal results in the game.
For example, in a series of matches in 1997 between Garry Kasparov and the IBM chess supercomputer Deep Blue, Kasparov lost a series of matches. After this, Garry disapproved of this strategy of playing chess.
When it comes to a game like poker, a game with incomplete information, things are a little different. A bot cannot win simply by following a limited set of rules because there is missing data; that is, one player does not know the other player’s hands. This conclusion applies to many other areas, such as gambling on the stock exchange, buying at auctions, and participating in business negotiations.
For example, you can still find the optimal set of rules for a game like Go, which is open, but has more possible moves than chess. AlphaGo, a software program developed by Google’s DeepMind, has confirmed this fact. On the other hand, if you want to win games with incomplete information, you need to constantly adjust your game strategy according to the data based on the play of your opponents. Playing your hand the same way will make you as predictable as a bot, and you will likely lose.
Poker has long attracted famous scientists such as Alan Turing and John von Neumann, who were among the first to become interested in thinking machines. And now this interest continues to rise.
Often poker is considered an art, rather than a science because it depends so much on intelligence and initiative and not on monotonous figures and calculations. However, today’s best poker bots cast doubt on this idea. At the same time, our understanding of how a bot and a human make a game strategy and make decisions is also changing.
In 2015, there was a very important event in the world of poker. Developers from the University of Alberta showed their poker bot, Cepheus, was able to solve a limited version of Texas Hold’em for two players, which is a one-on-one game with restrictions on maximum bets. The bot is played according to the equilibrium strategy, which in every single situation depends on the possible options with a certain probability. So, the player who follows such a strategy will not lose money for a long time.
It is worth noting that no one taught Cepheus any poker strategy. He learned by losing billions of simulated hands.
Can Success be Achieved in Other Types of Poker?
Nowadays, developers have shifted their attention to other types of poker. The limited version of Hold’em, solved by Cepheus, has a fairly solid framework, which makes it possible to study the strategy better. However, this significantly reduces the relevance of such studies regarding their use in the real world.
Without a doubt, no limit Hold’em is the next step in poker player vs. bot challenge, because this game is the most popular version of poker. The fact that the amount of the bet in this game is not limited, and the player can go all-in at any time, greatly complicates the task.
Some bots play no limit Hold’em with ease and even show some tactical thinking far beyond human ability. Gradually evolving, bots are starting to discover new ways of juggling risks and also finding innovative decision-making options for playing games with incomplete information.
All of the above begs the following question: Which aspects of our behavior can be considered human in nature and which can be used by thinking machines?
Although poker is a psychological game, it cannot be said that in this game only people can deceive each other; ie, on the bluff. In fact, today, the poker online bot can come up with the same decision based on the optimal strategy.
The best poker bots have taught each other to bluff, show aggression, and even manipulate their opponents. In the end, we can say that Kasparov’s expectations that computers will understand that it is sometimes profitable to play like a person, and not like a machine, are gradually coming true.
Conclusion
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