Improved international chess game method based on AlphaGo Zero

Abstract

The invention provides an improved international chess game method based on AlphaGo Zero, expands the application range of an AlphaGo Zero method in the field of man-machine games, and belongs to thefield of robot science and technology entertainment. The method comprises the following steps: adopting a hybrid network structure including a CNN, ResNet and a full connection layer capable of effectively avoiding gradient dispersion and obtaining optimal position convergence, and using a training network to output a strategy and an estimated value at the same time; 2) adopting a reinforcement learning strategy, performing training by using data generated by self-game (Self-Play) so that the problem of large data training scale of a sequential structure is solved, and optimizing a model in the game process; 3) training an optimization model by the neural network, defining a loss function, and selecting a corresponding optimizer to perform iterative updating in a loss reduction direction;4) evaluating the network model: playing chess by using the new model after being trained for a period of time and the model before being trained, and obtaining the performance of the current model according to the winning and losing bureau number to judge whether to iterate the model or not, and 5) performing visual interactive game test and evaluation by adopting third-party software.

Description

technical field [0001] The invention proposes an improved chess game method based on AlphaGo Zero, expands the application scope of the AlphaGo Zero method in the field of man-machine games, and belongs to the technical field of robot technology and entertainment. Background technique [0002] Human-computer game mechanism and its algorithm research Since the birth of the computer, people have not stopped exploring it. Human-computer game is an important branch of artificial intelligence. In the process of studying human-computer game, people have explored many new methods and new ideas of artificial intelligence including machine learning, which have had a profound impact on social life and academic research. . [0003] The reason why the present invention chooses chess as a research example of man-machine game is that in addition to the infinite charm of the game displayed by chess, the larger search space of chess is also more difficult to solve by traditional methods, s...

AI Technical Summary

Problems solved by technology

[0006] 2) Using reinforcement learning strategy, by using the data generated by self-play (Self-Play) for training, solve the problem of large-scale data training of sequential structure, and optimize the model during the game process;

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