大型多人在线角色扮演游戏的下一地点预测

摘要/Abstract

摘要： 近年来,大型多人在线角色扮演游戏(MMORPG)已经成为最流行的网络娱乐活动之一。MMORPG在游戏环境中形成虚拟社会,其中每个玩家扮演某个虚构角色,并控制该角色的大多数活动。游戏的迅猛发展累积了海量数据,其中包含游戏虚拟社会的语义和拓扑信息。研究者针对游戏数据开展了一系列研究工作,如玩家退出预测、游戏服务器整合等。游戏角色的下一地点预测对提升游戏体验、改善游戏设计和检测游戏机器人均有十分重要的意义。目前,该项预测任务主要使用统计分析完成。然而,由于游戏数据具有海量特征,因此需要一种自动化的计算方法。文中提出了基于隐马尔科夫模型的游戏角色下一地点预测模型,该模型能够考虑与位置特性相关的不可观测的属性,同时兼顾游戏角色前期行为的影响。实验结果表明,与现有方法相比,该方法具有建模直观的特点,在稠密分布的MMORPG数据中能够得到更准确的下一地点预测结果。

关键词: 大型多人在线角色扮演游戏, 下一位置预测, 隐马尔可夫模型, 游戏日志挖掘

Abstract: In recent years,massively multiplayer online role-playing games (MMORPG) has become one of the most popular Internet recreational activities.MMORPG creates virtual societies,in which each user plays a fictional character,and controls most of its activities.With rapid development of MMORPG,it has accumulated massive data,which contain semantic as well as topological information of virtual societies.Researchers have already carried out manystu-dies,such as player departure prediction and server consolidation.The task of next place prediction is crucial to enhance gaming experience,improve game design and game bot detection,and most of next place prediction methods are based on statistical analysis.However,it is difficult to apply these methods in practice due to the characteristic of large scale of game data,and an automatic computation method to be developed.This paper proposed a next place prediction algorithm based on hidden Markov model (HMM).The model considers location characteristics as unobservable parameters,and takes the effects of previous actions of each game character into consideration.Experimental results with real MMORPG dataset show that our approach is intuitive and has better performance in dense distributed data than other existing methods for the task of next place prediction of MMORPG.

Key words: Game data mining, Hidden Markov model, MMORPG, Next place prediction

中图分类号:

TP391

佟振明, 刘志鹏. 大型多人在线角色扮演游戏的下一地点预测[J]. 计算机科学, 2018, 45(11A): 453-457. https://doi.org/

TONG Zhen-ming, LIU Zhi-peng. Next Place Prediction of Massively Multiplayer Online Role-playing Games[J]. Computer Science, 2018, 45(11A): 453-457. https://doi.org/

参考文献

[1]NARDI B,HARRIS J.Strangers and friends:Collaborative play in World of Warcraft[C]∥International Handbook of Internet Research.Springer,2010:395-410.
[2]LEE Y T,CHEN K T,CHENG Y M,et al.World of Warcraft avatar history dataset[C]∥Proceedings of the Second Annual ACM Conference on Multimedia Systems.ACM,2011:123-128.
[3]TARNG P Y,CHEN K T,HUANG P.On prophesying online gamer departure[C]∥2009 8th Annual Workshop on Network and Systems Support for Games (NetGames).IEEE,2009:1-2.
[4]LEE Y T,CHEN K T.Is server consolidation beneficial to MMORPG? A case study of World of Warcraft[C]∥2010 IEEE 3rd International Conference on Cloud Computing (CLOUD).IEEE,2010:435-442.
[5]CHEN K T,PAO H K K,CHANG H C.Game bot identification based on manifold learning[C]∥Proceedings of the 7th ACM SIGCOMM Workshop on Network and System Support for Games.ACM,2008:21-26.
[6]CHEN K T,LIAO A,PAO H K K,et al.Game bot detection based on avatar trajectory[C]∥Entertainment Computing-ICEC 2008. Springer,2009:94-105.
[7]DUCHENEAUT N,YEE N,NICKELL E,et al.The life and death of online gaming communities:a look at guilds in world of warcraft[C]∥Proceedings of the SIGCHI Conference on Human Factors in Computing Systems.ACM,2007:839-848.
[8]DUCHENEAUT N,YEE N,NICKELL E,et al.Building an MMO with mass appeal a look at gameplay in world of warcraft[J].Games and Culture,2006,1(4):281-317.
[9]MITTERHOFER S,PLATZER C,KRUEGEL C,et al.Server-side bot detection in massive multiplayer online games[J].IEEE Security and Privacy,2009,7(3):29-36.
[10]PLATZER C.Sequence-based bot detection in massive multi-player online games[C]∥2011 8th International Conference on Information,Communications and Signal Processing (ICICS).IEEE,2011:1-5.
[11]ETTER V,KAFSI M,KAZEMI E.Been there,done that:What your mobility traces reveal about your behavior[C]∥Mobile Data Challenge by Nokia Workshop,in Conjunction with Int Conf on Pervasive Computing.2012.
[12]WANG J,PRABHALA B.Periodicity based next place prediction[C]∥Nokia Mobile Data Challenge 2012 Workshop Dedicated Task.Citeseer,2012.
[13]GAO H,TANG J,LIU H.Mobile location prediction in spatio-temporal context[C]∥Nokia Mobile Data Challenge Workshop.Citeseer,2012.
[14]BAUMANN P,KLEIMINGER W,SANTINI S.The influence of temporal and spatial features on the performance of next-place prediction algorithms[C]∥Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing.ACM,2013:449-458.
[15]TRAN L H,CATASTA M,MCDOWELL L K,et al.Next Place Prediction using Mobile Data[C]∥Proceedings of the Mobile Data Challenge Workshop (MDC 2012).2012.
[16]NOULAS A,SCELLATO S,LATHIA N,et al.Mining User Mobility Features for Next Place Prediction in Location-Based Services[C]∥ICDM.Citeseer,2012:1038-1043.
[17]DUDA R O,HART P E,STORK D G.Pattern classification[M].John Wiley & Sons,1999.

相关文章 15

[1]	费星瑞, 谢逸. 基于HMM-NN的用户点击流识别 Click Streams Recognition for Web Users Based on HMM-NN 计算机科学, 2022, 49(7): 340-349. https://doi.org/10.11896/jsjkx.210600127
[2]	王欣, 向明月, 李思颖, 赵若成. 基于隐马尔可夫模型的铁路出行团体关系预测研究 Relation Prediction for Railway Travelling Group Based on Hidden Markov Model 计算机科学, 2022, 49(6A): 247-255. https://doi.org/10.11896/jsjkx.210500001
[3]	张经, 杨健, 苏鹏. 语音识别中单音节识别研究综述 Survey of Monosyllable Recognition in Speech Recognition 计算机科学, 2020, 47(11A): 172-174. https://doi.org/10.11896/jsjkx.200200006
[4]	张成伟, 罗凤娥, 代毅. 基于数据挖掘的指定航班计划延误预测方法 Prediction Method of Flight Delay in Designated Flight Plan Based on Data Mining 计算机科学, 2020, 47(11A): 464-470. https://doi.org/10.11896/jsjkx.200600001
[5]	岳鑫, 杜军威, 胡强, 王延平. 一种故障树结构匹配算法及其应用 Fault Tree Structure Matching Algorithm and Its Application 计算机科学, 2018, 45(9): 202-206. https://doi.org/10.11896／j.issn.1002-137X.2018.09.033
[6]	宫法明,朱朋海. 基于自适应隐马尔可夫模型的石油领域文档分词 Word Segmentation Based on Adaptive Hidden Markov Model in Oilfield 计算机科学, 2018, 45(6A): 97-100.
[7]	张向刚,唐海,付常君,石宇亮. 一种基于隐马尔科夫模型的步态识别算法 Gait Recognition Algorithm Based on Hidden Markov Model 计算机科学, 2016, 43(7): 285-289. https://doi.org/10.11896/j.issn.1002-137X.2016.07.052
[8]	杨晓东,陈益强,于汉超,刘军发,李展歌. 面向可穿戴设备的超声波手势识别方法 Ultrasonic Waves Based Gesture Recognition Method for Wearable Equipment 计算机科学, 2015, 42(10): 20-24.
[9]	丁勇,朱辉生,曹红根. 基于混合EHMM模型的数据流预测 Data Flow Forecasting Based on Hybrid EHMM Models 计算机科学, 2014, 41(Z6): 391-393.
[10]	矫健,张仰森. 基于隐马尔可夫模型的查询扩展方法 Query Expansion Method Based on Hidden Markov Model 计算机科学, 2014, 41(12): 168-171. https://doi.org/10.11896/j.issn.1002-137X.2014.12.036
[11]	谢柏林,蒋盛益,张倩生. 基于请求关键词的应用层DDoS攻击检测方法 Application-layer DDoS Attack Detection Based on Request Keywords 计算机科学, 2013, 40(7): 121-125.
[12]	李荣,胡志军,郑家恒. 基于遗传算法和隐马尔可夫模型的Web信息抽取的改进 Improvement of Web Information Extraction Based on Genetic Algorithm and Hidden Markov Model 计算机科学, 2012, 39(3): 200-205.
[13]	马力,谭薇,李培. 基于Web访问信息的用户兴趣迁移模式的研究 Research of iJser Interest Drift Pattern Based on Web Access Information 计算机科学, 2011, 38(5): 175-177.
[14]	谢铭，吴产乐. 用户信息保护下的学习资源知识点自动提取 Topic Extracting with User Information Protection on Web 计算机科学, 2011, 38(3): 203-205.
[15]	于美娟,马希荣. 基于HMM方法的动态手势识别技术的改进 Improvement of Dynamic Hand Gesture Recognition Technology Based on HMM Method 计算机科学, 2011, 38(1): 251-252.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed