Player preference and style in a leading mobile card game

Cowling, Peter I, Devlin, Sam, Powley, Edward ORCID logoORCID:, Whitehouse, Daniel and Rollason, Jeff (2015) Player preference and style in a leading mobile card game. IEEE Transactions on Computational Intelligence and AI in Games, 7 (3). pp. 233-242. ISSN 1943-068X

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Abstract / Summary

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.

Item Type: Article
Identification Number: 10.1109/TCIAIG.2014.2357174
ISSN: 1943-068X
Subjects: Computer Science, Information & General Works
Technology > Digital Works > Digital Games
Courses by Department: The Games Academy > Computing for Games
Depositing User: Edward Powley
Date Deposited: 23 Jun 2017 12:31
Last Modified: 11 Nov 2022 16:30


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