Automatic level Generation for Tower Defense Games

被引:0
|
作者
Du, Yu [1 ]
Li, Jian [1 ]
Hou, Xiao [2 ]
Lu, Hengtong [1 ]
Liu, Simon Cheng [2 ]
Guo, Xianghao [2 ]
Yang, Kehan [1 ]
Tang, Qinting [1 ]
机构
[1] Beijing Univ Posts & Telecorrununicat, Coll Comp Sci & Thchnol, Beijing, Peoples R China
[2] LevelupAI, Beijing, Peoples R China
来源
PROCEEDINGS OF 2019 IEEE 3RD INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2019) | 2019年
关键词
Procedural Content Generation; games; evolutionary algorithm; search; automatic design;
D O I
10.1109/itnec.2019.8728989
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We created a new method to automatically generate levels for a commercial-grade tower defense game Kingdom Kush: Frontiers (KRF) by means of Procedural Content Generation(PCG). Our research focuses on path generation and monster sequence generation. Firstly, we designed a mathematical representation of the game's path using geometric rules, and then we used search algorithms to develop an algorithm, which can generate new paths that are similar to the paths in original games. We implemented monster sequence generation with genetic algorithm in which we designed a representation of genes that reused some human-designed elements. In addition, we also designed a fitness function to make sure the generated level has moderate difficulty and playability. Finally, we automatically generated new levels for KRF with the combine of path generation and monster sequence generation. We used a turing test to show that our PCG levels are hard to be distinguished from the original levels.
引用
收藏
页码:670 / 676
页数:7
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