Scientist Creates Unbeatable Poker Bot?

Norwegian engineer Fredrik Dahl claims to have developed a poker bot able to best all but the very top 100 elite players in the world.

Online Poker Bot

Norwegian engineer Fredrik Dahl has been studying neural networks-based artificial intelligence and poker is an excellent field for his experiments, as the highest levels of the game require creativity instead of simply observing patterns and exploiting weaknesses with general strategies.

According to the New York Times, Dahl has achieved some impressive results in modeling the human brain. He has created a program that thinks and learns in a way that it has become virtually unbeatable in poker for most players.

“Functioning much like an extremely focused, one-dimensional version of the human brain, these complex computer algorithms develop strategies that emerge through so many repetitive mathematical calculations that few humans could reproduce, much less endure them,” the paper writes.

The bot is able to learn from its mistakes, adapt to its opponents and notice changes in their strategy. Reportedly, it has developed itself through billions of hands to be a conscious, unpredictable player with an estimated top of 100 players in the world able to steadily beat it.

“Gamblers might win a given hand out of sheer luck, but over an extended period, as the impact of luck evens out, they must overcome carefully trained neural nets that self-learned to play aggressively and unpredictably with the expertise of a skilled professional,” and which are “responding to opponents’ moves and pursuing optimal strategies,” the New York Times reports.

The bot will be first publicly shown in the Global Gaming Expo in Las Vegas and it will be made available for play in live casinos in the US thereafter. Its developer, Dahl used to work for the Norwegian Ministry of defense and was involved in government projects to develop software that self-develops and can be applied for military purposes.

Read the entire report from the New York Times here.