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摘要翻译：
虚拟瘟疫是一种影响行为的属性在大型多人在线游戏(MMOG)中的角色之间传播的过程。MMOG个体构成了一个合成群体，这个游戏可以被看作是一种用于研究疾病传播的交互可执行模型，尽管是一种非常特殊的模型。对于维护MMOG的游戏开发人员来说，识别、监视并最终控制虚拟瘟疫是很重要的，不管它是如何开始的。使用流行病学领域的工具、方法和理论来做这件事的前景似乎很自然，也很有吸引力。我们将讨论这一前景的可行性，首先考虑流行病学中使用的一些基本措施，然后指出现实世界流行病和虚拟瘟疫之间的差异。我们还通过流行病学模型提出了MMOG显影剂控制的方向。我们的目的是了解虚拟瘟疫的性质，而不是试图消除它们或减轻它们的影响，就像在真正的传染病情况下一样。
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英文标题：
《Modeling Epidemic Spread in Synthetic Populations - Virtual Plagues in
Massively Multiplayer Online Games》
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作者：
Magnus Boman and Stefan J. Johansson
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最新提交年份：
2007
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Computers and Society 计算机与社会
分类描述：Covers impact of computers on society, computer ethics, information technology and public policy, legal aspects of computing, computers and education. Roughly includes material in ACM Subject Classes K.0, K.2, K.3, K.4, K.5, and K.7.
涵盖计算机对社会的影响、计算机伦理、信息技术和公共政策、计算机的法律方面、计算机和教育。大致包括ACM学科类K.0、K.2、K.3、K.4、K.5和K.7中的材料。
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一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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一级分类：Computer Science 计算机科学
二级分类：Multiagent Systems 多智能体系统
分类描述：Covers multiagent systems, distributed artificial intelligence, intelligent agents, coordinated interactions. and practical applications. Roughly covers ACM Subject Class I.2.11.
涵盖多Agent系统、分布式人工智能、智能Agent、协调交互。和实际应用。大致涵盖ACM科目I.2.11类。
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英文摘要：
A virtual plague is a process in which a behavior-affecting property spreads among characters in a Massively Multiplayer Online Game (MMOG). The MMOG individuals constitute a synthetic population, and the game can be seen as a form of interactive executable model for studying disease spread, albeit of a very special kind. To a game developer maintaining an MMOG, recognizing, monitoring, and ultimately controlling a virtual plague is important, regardless of how it was initiated. The prospect of using tools, methods and theory from the field of epidemiology to do this seems natural and appealing. We will address the feasibility of such a prospect, first by considering some basic measures used in epidemiology, then by pointing out the differences between real world epidemics and virtual plagues. We also suggest directions for MMOG developer control through epidemiological modeling. Our aim is understanding the properties of virtual plagues, rather than trying to eliminate them or mitigate their effects, as would be in the case of real infectious disease.
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PDF链接：
https://arxiv.org/pdf/0705.4584
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