Nested Monte-Carlo Search with simulation reduction

被引：2

作者：

Akiyama, Haruhiko ^{[1
]}

Komiya, Kanako ^{[2
]}

Kotani, Yoshiyuki ^{[2
]}

机构：

[1] Tokyo Univ Agr & Technol, Dept Comp & Informat Sci, Tokyo, Japan

[2] Tokyo Univ Agr & Technol, Inst Engn, Tokyo, Japan

来源：

KNOWLEDGE-BASED SYSTEMS | 2012年 / 34卷

关键词：

Nested Monte-Carlo Search; All-Moves-As-First (AMAF); Single-player games; Morpion Solitaire; Random simulation;

D O I：

10.1016/j.knosys.2011.11.015

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The execution time of Nested Monte-Carlo Search for Morpion Solitaire, a single-player game, increases exponentially with the level of the nested search. We investigated the use of two methods for reducing the execution time in order to enable a deeper nested search: simply reducing the number of lower level searches by a constant rate and using All-Moves-As-First heuristic to the reduction in the number of lower level searches. Testing showed the latter is more effective. Using it, we achieved a new world record of 146 moves for a computer search for the touching version of Morpion Solitaire. (c) 2011 Elsevier B.V. All rights reserved.

引用

页码：12 / 20

页数：9

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