手机纸牌游戏中的玩家偏好和风格

P. Cowling, Sam Devlin, E. Powley, D. Whitehouse, Jeff Rollason
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引用次数: 16

摘要

在发行前调整游戏难度需要仔细考虑。如果游戏太难或太简单,玩家很快就会对游戏失去兴趣。在游戏发行前评估玩家的反应通常是不准确的。然而,现代游戏现在可以收集足够的数据,在部署后执行大规模分析,并基于这些见解更新产品。《AI Factory Spades》目前是b谷歌Play商店中排名最高的《Spades》游戏。通过与开发者合作,我们收集了27592款游戏的玩法数据,并使用谷歌Analytics收集了99866款游戏的输赢数据。利用收集到的数据,本研究分析了我们之前在游戏中开发和部署的信息集蒙特卡罗树搜索玩家的难度和行为。本研究的数据收集和分析方法具有普遍适用性。同样的工作流程也可以用于分析任何游戏中的难度和典型玩家或对手行为。此外,在部署后解决难度问题或非人类对手可以积极影响玩家留存率。
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Player Preference and Style in a Leading Mobile Card Game
Tuning game difficulty prior to release requires careful consideration. Players can quickly lose interest in a game if it is too hard or too easy. Assessing how players will cope prior to release is often inaccurate. However, modern games can now collect sufficient data to perform large scale analysis post deployment and update the product based on these insights. AI Factory Spades is currently the top rated Spades game in the Google Play store. In collaboration with the developers, we have collected gameplay data from 27 592 games and statistics regarding wins/losses for 99 866 games using Google Analytics. Using the data collected, this study analyses the difficulty and behavior of an Information Set Monte Carlo Tree Search player we developed and deployed in the game previously. The methods of data collection and analysis presented in this study are generally applicable. The same workflow could be used to analyze the difficulty and typical player or opponent behavior in any game. Furthermore, addressing issues of difficulty or nonhuman-like opponents postdeployment can positively affect player retention.
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来源期刊
IEEE Transactions on Computational Intelligence and AI in Games
IEEE Transactions on Computational Intelligence and AI in Games COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, SOFTWARE ENGINEERING
CiteScore
4.60
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: Cessation. The IEEE Transactions on Computational Intelligence and AI in Games (T-CIAIG) publishes archival journal quality original papers in computational intelligence and related areas in artificial intelligence applied to games, including but not limited to videogames, mathematical games, human–computer interactions in games, and games involving physical objects. Emphasis is placed on the use of these methods to improve performance in and understanding of the dynamics of games, as well as gaining insight into the properties of the methods as applied to games. It also includes using games as a platform for building intelligent embedded agents for the real world. Papers connecting games to all areas of computational intelligence and traditional AI are considered.
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