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Earlier this year, amateur Go players were among the game’s top-ranked AI systems. They did this using strategies developed with the help of researchers in programs designed to probe weaknesses in systems like KataGo.Winning turns out to be just part of a broader Go renaissance that’s seeing human players get more creative
A recent study published in the journal researchers from the City University of Hong Kong and Yale University have found that human Go players have become less predictable in recent years. , researchers reached that conclusion by analyzing a dataset of over 5.8 million Go moves made during professional play between 1950 and 2021. Playing the game with the help of a “superhuman” Go AI, they created a statistic called the “Decision Quality Index” or DQI for short.
After assigning a DQI score to every move in the dataset, the team found that the quality of professional play improved little year-over-year prior to 2016. At best, the team saw a median positive annual DQI change of 0.2. In some years, even the overall quality of play has declined. However, since the rise of superhuman AI in 2018, the median DQI value has changed by more than 0.7. During the same period, professional players adopted more novel strategies. In 2018, in 88% of games he set up combinations of plays never seen before by players in 88% of games, up from 63% in 2015.
“Our findings suggest that the development of superhuman AI programs may have prompted human players to break away from traditional strategies and explore new moves. , could have improved decision-making,” the team wrote.
This is an interesting change, but not counterintuitive when you think about it. As Professor Stuart Russell at the University of California, Berkeley said: new scientist“It is not surprising that players who train against a machine tend to make more moves than the machine approves.”
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