General Game Heuristic Prediction Based on Ludeme Descriptions

被引：1

作者：

Stephenson, Matthew ^{[1
]}

Soemers, Dennis J. N. J. ^{[1
]}

Piette, Eric ^{[1
]}

Browne, Cameron ^{[1
]}

机构：

[1] Maastricht Univ, Dept Data Sci & Knowledge Engn, Maastricht, Netherlands

来源：

2021 IEEE CONFERENCE ON GAMES (COG) | 2021年

基金：

欧洲研究理事会;

关键词：

Ludii; Heuristics; Ludemes; General Game Playing; Data Mining; Supervised Learning;

D O I：

10.1109/COG52621.2021.9619052

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper investigates the performance of different general-game-playing heuristics for games in the Ludii general game system. Based on these results, we train several regression learning models to predict the performance of these heuristics based on each game's description file. We also provide a condensed analysis of the games available in Ludii, and the different ludemes that define them.

引用

页码：878 / 881

页数：4

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