Online Resource
Darcy & Roy Press Co. Ltd.
;
2022
In:
Highlights in Science, Engineering and Technology Vol. 12 ( 2022-08-26), p. 13-24
In:
Highlights in Science, Engineering and Technology, Darcy & Roy Press Co. Ltd., Vol. 12 ( 2022-08-26), p. 13-24
Abstract:
Computer Games are an important aspect of Artificial Intelligence (AI) which has produced many representative algorithms of optimal strategies. Therefore, many AI researchers have applied game theory to various board games in an attempt to find the essence of games and grasp the core of AI behaviour. AlphaGo is a very famous and typical chess-playing program that uses Monte Carlo tree search (MCTS) to estimate the value of each node in the search tree and optimize the possible results. Chinese chess is one of the traditional chess versions with its typical strategy. However, due to its late start and high complexity, there are many more technical problems to be solved. In this paper, we recommend two commonly used search frameworks for Chinese chess: the minimax algorithm and the alpha-beta pruning algorithm. On this basis, to deal with the complex and changeable situation, the Chinese chess algorithm based on Monte Carlo tree search and appropriate neural network evaluation function is studied.
Type of Medium:
Online Resource
ISSN:
2791-0210
DOI:
10.54097/hset.v12i.1358
Language:
Unknown
Publisher:
Darcy & Roy Press Co. Ltd.
Publication Date:
2022
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