Open AccessDesign and improvement of the pruning algorithm of the Chinese chess in the computer games
Author(s) -
Tao Jun,
Wu Gui,
Pan Xueliang
Publication year - 2020
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.1169
Subject(s) - pruning , computer science , computer chess , field (mathematics) , search algorithm , algorithm , computer game , task (project management) , iterative deepening depth first search , tree (set theory) , search tree , table (database) , game tree , core (optical fiber) , depth first search , artificial intelligence , beam search , sequential game , mathematics , incremental heuristic search , game theory , data mining , multimedia , engineering , systems engineering , mathematical economics , history , mathematical analysis , archaeology , biology , telecommunications , agronomy , championship , pure mathematics
Computer games have always been considered to be the most challenging task in the field of artificial intelligence specially the Chinese chess as an example. The core technology of the computer games is the search. This work is studied to research an improved pruning strategy in order to achieve a deeper level search of the game tree in a limited time. On the basis of the traditional alpha–beta search algorithm, the worthless nodes are discarded to be never searched by introducing the deep iterative, history table and other auxiliary methods of pruning. The number of nodes searched is effectively reduced to make the pruning earlier to shorten the search time. At the same time, its search depth is higher than the original search algorithm. The advanced and modified algorithm is proved to be practical and applicative by experimentations and tests of computer games system provided in this study.