Y. Duan, J. Edwards, P. Robins
{"title":"Experiences with EXGAME: an expert system for playing a competitive business game","authors":"Y. Duan, J. Edwards, P. Robins","doi":"10.1002/(SICI)1099-1174(199803)7:1%3C1::AID-ISAF139%3E3.0.CO;2-W","DOIUrl":null,"url":null,"abstract":"This paper looks at expert systems in management, by using a business game as an experimental vehicle. An expert system called EXGAME was developed to play a business game, which is normally played by students, with minimal human intervention. This paper concentrates on the effectiveness of EXGAME as compared with human players for tasks at different levels. EXGAME was able to replace human players in decision making at the operational level, and indeed outperform them. However, it proved to be impractical to replace human input at the strategic level. The paper also sheds some light on the problems of trying to build an expert system when there is no real expert. A combination of a modular knowledge-base structure and a process of ‘learning by experimentation’ was effective in this case; it is suggested that this may be an appropriate development strategy in other similar situations. © 1998 John Wiley & Sons, Ltd.","PeriodicalId":153549,"journal":{"name":"Intell. Syst. Account. Finance Manag.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intell. Syst. Account. Finance Manag.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/(SICI)1099-1174(199803)7:1%3C1::AID-ISAF139%3E3.0.CO;2-W","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
EXGAME的经验:一个玩竞争性商业游戏的专家系统
本文通过使用商业游戏作为实验工具来研究管理中的专家系统。开发了一个名为EXGAME的专家系统来玩通常由学生玩的商业游戏,人工干预最少。本文主要研究了EXGAME在不同级别的任务中与人类玩家相比的有效性。EXGAME能够在操作层面上取代人类玩家的决策,并且确实比他们表现得更好。然而,事实证明,在战略层面取代人力投入是不切实际的。本文还对在没有真正的专家的情况下试图建立专家系统的问题进行了一些阐述。在这种情况下,模块化知识库结构和“通过实验学习”过程的结合是有效的;有人建议,在其他类似情况下,这可能是一种适当的发展战略。©1998 John Wiley & Sons, Ltd
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