Wuji: Automatic online combat game testing using evolutionary deep reinforcement learning

Yan Zheng, Changjie Fan, Xiaofei Xie, Ting Su, Lei Ma, Jianye Hao, Zhaopeng Meng, Yang Liu, Ruimin Shen, Yingfeng Chen

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

20 被引用数 (Scopus)

抄録

Game testing has been long recognized as a notoriously challenging task, which mainly relies on manual playing and scripting based testing in game industry. Even until recently, automated game testing still remains to be largely untouched niche. A key challenge is that game testing often requires to play the game as a sequential decision process. A bug may only be triggered until completing certain difficult intermediate tasks, which requires a certain level of intelligence. The recent success of deep reinforcement learning (DRL) sheds light on advancing automated game testing, without human competitive intelligent support. However, the existing DRLs mostly focus on winning the game rather than game testing. To bridge the gap, in this paper, we first perform an in-depth analysis of 1349 real bugs from four real-world commercial game products. Based on this, we propose four oracles to support automated game testing, and further propose Wuji, an on-the-fly game testing framework, which leverages evolutionary algorithms, DRL and multi-objective optimization to perform automatic game testing. Wuji balances between winning the game and exploring the space of the game. Winning the game allows the agent to make progress in the game, while space exploration increases the possibility of discovering bugs. We conduct a large-scale evaluation on a simple game and two popular commercial games. The results demonstrate the effectiveness of Wuji in exploring space and detecting bugs. Moreover, Wuji found 3 previously unknown bugs, which have been confirmed by the developers, in the commercial games.

本文言語英語
ホスト出版物のタイトルProceedings - 2019 34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ページ772-784
ページ数13
ISBN(電子版)9781728125084
DOI
出版ステータス出版済み - 11 2019
イベント34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019 - San Diego, 米国
継続期間: 11 10 201911 15 2019

出版物シリーズ

名前Proceedings - 2019 34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019

会議

会議34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019
国/地域米国
CitySan Diego
Period11/10/1911/15/19

All Science Journal Classification (ASJC) codes

  • コンピュータ ネットワークおよび通信
  • ソフトウェア
  • 制御と最適化

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