Traditional Culture Encyclopedia - Traditional culture - Which of the following methods is used to learn alphago?
Which of the following methods is used to learn alphago?
1. Learn a lot about human chess players: This is AlphaGo's original learning method. By learning a lot about human chess players, we can understand and simulate human chess strategies and skills.
2. Self-deep learning: After completing the initial learning, AlphaGo began to enter a complete self-deep learning stage. At this stage, it completely abandons the thinking mode of human chess players, but learns Go independently in its own way through "left-right fighting".
3. Combining the advantages of supervised learning and reinforcement learning: In the self-deep learning stage, AlphaGo combines the advantages of supervised learning and reinforcement learning. Specifically, it forms a strategy network through training, takes the situation on the chessboard as input information, and forms a probability distribution for all feasible positions.
4. Training the value network to predict the self-game: AlphaGo also trained a value network to predict the results of all feasible positions by learning the self-game prediction. The standard is-1 (the absolute victory of the opponent) to1(the absolute victory of AlphaGo).
Through the above learning methods, AlphaGo continuously optimizes and improves its Go technology, and finally reaches a very high level.
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