Alpha Go Artificial Intelligence
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Alpha Go is an Go artificial intelligence program developed by David Silver, Ai Jia Huang, and Damies Hasabis of Google’s Deep Mind company and their team. The program uses the "value network" to calculate the situation and the "strategic network" to choose the next. In October 2015, Alpha Go scored a 5:0 victory over the European Go champion and professional second-stage player Fan Yan. In March 2016, he played against the world Go champion and professional nine-segment player Li Shishi and won with a total score of 4:1.
Alpha Go's main working principle is "deep learning", which improves chess by collaborating with two different neural networks "brains." . "Deep learning" refers to a multi-layered artificial neural network and methods of training it, which are structurally similar to those identified by the Google image search engine. They start with a multi-layered heuristic two-dimensional filter and deal with the positioning of the chess board, just like the image classifier network processes images. After filtering, 13 completely connected layers of the neural network produce a judgment of what they see. These layers can do classification and logical reasoning.
The network checks the results through repeated training, and then adjusts the calibration parameters to make the next execution better. This processor has a lot of random elements, so it is impossible for people to know exactly how the network "thinks", but more training will allow it to evolve even better.
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