Search-based procedural content generation for GVG-LG

被引：8
|
作者：
Zafar, Adeel [1 ]
Mujtaba, Hasan [2 ]
Beg, Mirza Omer [2 ]
机构：
[1] Riphah Int Univ, Islamabad, Pakistan
[2] Natl Univ Comp & Emerging Sci, Islamabad, Pakistan
来源：
APPLIED SOFT COMPUTING | 2020年 / 86卷
关键词：
Genetic algorithm; Procedural content generation; Search-based procedural content generation; General video game level generation;
D O I：
10.1016/j.asoc.2019.105909
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Search-based Procedural Content Generation has been proven an efficient technique for the generation of different and diverse types of content. In this article, we generate general levels for 2D games using the FI2POP genetic algorithm. Generating entertaining levels is subjective. Therefore in this work, we focus on the aesthetics and difficulty of a level. For experimentation purposes, we generated levels for five different games in the General Video Game Level Generation track. Our results indicate that the generated levels are symmetrical, balanced, dense and reachable. (C) 2019 Elsevier B.V. All rights reserved.
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页数：9
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