Four months later, AlphaGo took part in the Future of Go Summit in China, the birthplace of Go. This online player achieved 60 straight wins in time-control games against top international players. In January 2017, we revealed an improved, online version of AlphaGo called Master. Players of all levels have extensively examined these moves ever since. During the games, AlphaGo played several inventive winning moves, several of which - including move 37 in game two - were so surprising that they upended hundreds of years of wisdom. This was the first time a computer Go player had ever received the accolade. The game earned AlphaGo a 9 dan professional ranking, the highest certification. This landmark achievement was a decade ahead of its time. AlphaGo's 4-1 victory in Seoul, South Korea, on March 2016 was watched by over 200 million people worldwide. AlphaGo won the first ever game against a Go professional with a score of 5-0.ĪlphaGo then competed against legendary Go player Mr Lee Sedol, the winner of 18 world titles, who is widely considered the greatest player of the past decade. In October 2015, AlphaGo played its first match against the reigning three-time European Champion, Mr Fan Hui. AlphaGo went on to defeat Go world champions in different global arenas and arguably became the greatest Go player of all time. This process is known as reinforcement learning. Over time, AlphaGo improved and became increasingly stronger and better at learning and decision-making. Then we had it play against different versions of itself thousands of times, each time learning from its mistakes. We introduced AlphaGo to numerous amateur games to help it develop an understanding of reasonable human play. The other neural network, the “value network”, predicts the winner of the game. One neural network, the “policy network”, selects the next move to play. These neural networks take a description of the Go board as an input and process it through a number of different network layers containing millions of neuron-like connections. We created AlphaGo, a computer program that combines advanced search tree with deep neural networks. When you have finished making the moves, click the moved piece again, and the computer will start to take its turn.To capture the intuitive aspect of the game, we needed a new approach. The available spots for movement are highlighted in red when a marble is selected. Note that a piece cannot end its move on the 4 topmost rows of the bases other than its own or its target base, but can jump to it and jump out of it immediately. For instance, if no empty spot is located between the moving piece and the other piece, then the moving piece can be moved to the first empty space after the other piece on the same straight line and when an empty spot is located between the moving piece and the other piece, the jumping piece can be moved to the second empty space after the other piece on the same straight line. The distance of a jump depends on the number of empty spots between the moving piece and the target piece. During your turn, you can click to move one of your pieces to an adjacent empty space, or jump over other pieces for consecutive hops. You and the computer will take turns to make the moves. The 10 blue marbles on your side are placed in the blue area, while the 10 green pieces of the computer are located in the green base. When the game starts, you will be given a checkerboard in the shape of a hexagram, and the board is divided into 6 bases of different colors. Challenge your mind and try various strategies as you battle with the computer in this traditional board game! Your target is to move all your marbles to the enemy base before your opponent does so.
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