PRAGUE, March 3 (Xinhua) -- DeepStack, a computer program developed by Czech and Canadian scientists, has been the first algorithm that has defeated professional poker players, a Czech university spokeswoman said Friday.
According to Libuse Petrzilkova, spokeswoman for the Electrical Engineering Faculty of the Czech Technical University (CVUT), the DeepStack program is developed by a ten-member team from the CVUT, Charles University (UK) in Prague and the University of Alberta in Canada for nearly a year.
It was a long-standing challenge for artificial intelligence to beat professional players in poker.
According to the team, DeepStack is important for practical application because in everyday life there are many situations in which people make decisions based on imperfect information.
DeepStack makes it possible to calculate an appropriate strategy when a particular situation occurs, without the need to first take into account the whole game, which was the prevailing approach until now.
This change was enabled by the development of machine learning through deep artificial neural networks. In case of DeepStack, the neural network assesses poker situations. It is in fact a form of intuition that the mathematical algorithm applies to make the right decisions.
In December 2016, a group of 33 professional players that the International Federation of Poker chose from 17 countries and regions played the most popular variant of poker, no-limit Texas hold'em, against DeepStack.
All players had the opportunity to take part in 3,000 games in four weeks. DeepStack defeated all 11 players who played all 3,000 games also individually and only in one case the victory was not statistically significant.
DeepStack can play poker faster than people. It needs three seconds to make a decision on average, according to the team.
