Real-time challenge balance in an RTS game using rtNEAT

被引：39

作者：

Olesen, Jacob Kaae ^{[1
]}

Yannakakis, Georgios N. ^{[2
]}

Hallam, John ^{[1
]}

机构：

[1] Univ South Denmark, Maersk McKinney Moller Inst, Campusvej 55, DK-5230 Odense, Denmark

[2] IT Univ Copenhagen, Ctr Comp Games Res, DK-2300 Copenhagen, Denmark

来源：

2008 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND GAMES | 2008年

关键词：

D O I：

10.1109/CIG.2008.5035625

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 explores using the NEAT and rtNEAT neuro-evolution methodologies to generate intelligent opponents in real-time strategy (RTS) games. The main objective is to adapt the challenge generated by the game opponents to match the skill of a player in real-time, ultimately leading to a higher entertainment value perceived by a human player of the game. Results indicate the effectiveness of NEAT and rtNEAT but demonstrate their limitations for use in real-time strategy games.

引用

页码：87 / +

页数：2