玩家自适应《洞穴探险》关卡生成

David Stammer, Tobias Günther, M. Preuss
{"title":"玩家自适应《洞穴探险》关卡生成","authors":"David Stammer, Tobias Günther, M. Preuss","doi":"10.1109/CIG.2015.7317948","DOIUrl":null,"url":null,"abstract":"Procedural Content Generation (PCG) is nowadays widely applied to many different aspects of computer games. However, it can do more than to assist level designers during game creation. It can generate personalized levels according to the tastes and abilities of players online. This has already been demonstrated for (largely 1D) scrolling games and we show in this work how personalized, difficulty-adjusted levels can be generated for the more complex 2D platformer Spelunky. As direct and indirect player feedback is taken into account, the method may be filed under the Experience-Driven PCG approach. Our approach is based on a rather generic rule set that may also be transferred to similar games. We also present a user study showing that most users appreciate the online adaptation but are especially critical about making the game easier to play at any time.","PeriodicalId":244862,"journal":{"name":"2015 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Player-adaptive Spelunky level generation\",\"authors\":\"David Stammer, Tobias Günther, M. Preuss\",\"doi\":\"10.1109/CIG.2015.7317948\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Procedural Content Generation (PCG) is nowadays widely applied to many different aspects of computer games. However, it can do more than to assist level designers during game creation. It can generate personalized levels according to the tastes and abilities of players online. This has already been demonstrated for (largely 1D) scrolling games and we show in this work how personalized, difficulty-adjusted levels can be generated for the more complex 2D platformer Spelunky. As direct and indirect player feedback is taken into account, the method may be filed under the Experience-Driven PCG approach. Our approach is based on a rather generic rule set that may also be transferred to similar games. We also present a user study showing that most users appreciate the online adaptation but are especially critical about making the game easier to play at any time.\",\"PeriodicalId\":244862,\"journal\":{\"name\":\"2015 IEEE Conference on Computational Intelligence and Games (CIG)\",\"volume\":\"131 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Conference on Computational Intelligence and Games (CIG)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIG.2015.7317948\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Conference on Computational Intelligence and Games (CIG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIG.2015.7317948","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

摘要

如今,程序内容生成(PCG)被广泛应用于电脑游戏的许多不同方面。然而,它可以做的不仅仅是在游戏创作过程中帮助关卡设计师。它可以根据在线玩家的品味和能力生成个性化的关卡。这已经在(主要是1D)滚动游戏中得到了证明,我们在此展示了如何为更复杂的2D平台游戏《洞穴探险》生成个性化、难度调整的关卡。考虑到玩家的直接和间接反馈,这种方法可以归为体验驱动型PCG方法。我们的方法是基于一个相当通用的规则集,也可以转移到类似的游戏中。我们还提供了一项用户研究,显示大多数用户都喜欢在线调整,但对于让游戏在任何时候都更容易玩尤其重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Player-adaptive Spelunky level generation
Procedural Content Generation (PCG) is nowadays widely applied to many different aspects of computer games. However, it can do more than to assist level designers during game creation. It can generate personalized levels according to the tastes and abilities of players online. This has already been demonstrated for (largely 1D) scrolling games and we show in this work how personalized, difficulty-adjusted levels can be generated for the more complex 2D platformer Spelunky. As direct and indirect player feedback is taken into account, the method may be filed under the Experience-Driven PCG approach. Our approach is based on a rather generic rule set that may also be transferred to similar games. We also present a user study showing that most users appreciate the online adaptation but are especially critical about making the game easier to play at any time.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信