Design And Implementation Of Chinese Chess Self-game And Reinforcement Learning System

In recent years,with the rapid development of search algorithms,machine learning algorithms,and hardware equipment,the level of computer games has continued to improve,and they have defeated human world champions in various chess categories such as Go,Chess,and Shogi.For a long time,the search algorithms of many Chinese chess projects have been traditional pruning algorithms,or focused on the optimization based on this algorithm.In addition to the huge computing power required to run the entire system,the research on Chinese chess in artificial intelligence is relatively behind.In view of the above problems,this paper proposes a new model of combining reinforcement learning and Monte Carlo search algorithm to realize the Chinese chess self-play and reinforcement learning system,and make the system can master chess skills without human chess record data.The main research work of this paper is as follows:1.Design and implement a set of Chinese chess self-play and reinforcement learning system,which does not require human chess record data and supervision,and is trained and improved through self-learning.2.Design and implement a Monte Carlo search algorithm suitable for Chinese Chess,and apply it to the Chinese Chess self-play module to generate chess record data through continuous self-play.3.Design and build a set of neural network structure suitable for the Chinese chess game system.The neural network will provide chess suggestions during the Monte Carlo search process,and train the network model through the chess record data generated by the self-match game.4.Based on the Chinese chess self-game and reinforcement learning system,the algorithm optimization and parameter adjustment methods are proposed,which mainly include improving the search algorithm to improve the system efficiency and flexibly adjusting the neural network parameters to train a better network model.The research content of this paper helps to improve the performance of the Chinese chess game system and improve the traditional search and evaluation algorithms.It can also inspire similar game problems in other fields and help promote the development of artificial intelligence in my country.