Go is a game that has been played in China for over 2000 years.
Using a traditional Chinese board game and artificial intelligence, researchers at the University of Sydney and Charles Sturt University have gained new insight into how expertise develops. The findings, published this month in Nature's scientific reports , will improve our understanding of how we think and help to develop more flexible artificial intelligences. "In a rare achievement we used artificial neural networks, made up of hundreds of thousands of neurons each, to model how an expert rapidly evaluates a situation and narrows their choices down to the best options," said lead author Michael Harré from the University's School of Psychology. "As a species we are specialists, we can become experts in the most remarkably abstract tasks, but it has proven to be incredibly difficult to reproduce this because we understand it so poorly. This research has taken a significant step in our understanding by replicating the unconscious mental processes of experts in an artificial neural network and applying it to one of the most complex games we play today." The researchers used thousands of records of professional and amateur matches of Go, a game for two players which originated in China over 2000 years ago. "Using the data from these matches we replayed the amateur and professional games using our artificial neural networks," said Harré. "What we were able to do is model the mental processes that experts develop by using simplified versions of biological networks.
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