Johns Hopkins University, 313 Ames Hall, Baltimore, MA 21218, USA.
Risk Anal. 2012 Jul;32(7):1117-21. doi: 10.1111/j.1539-6924.2011.01737.x. Epub 2011 Dec 8.
Intelligent adversary modeling has become increasingly important for risk analysis, and a number of different approaches have been proposed for incorporating intelligent adversaries in risk analysis models. However, these approaches are based on a range of often-implicit assumptions about the desirable properties of intelligent adversary models. This "Perspective" paper aims to further risk analysis for situations involving intelligent adversaries by fostering a discussion of the desirable properties for these models. A set of four basic necessary conditions for intelligent adversary models is proposed and discussed. These are: (1) behavioral accuracy to the degree possible, (2) computational tractability to support decision making, (3) explicit consideration of uncertainty, and (4) ability to gain confidence in the model. It is hoped that these suggested necessary conditions foster discussion about the goals and assumptions underlying intelligent adversary modeling in risk analysis.
智能对手建模对于风险分析变得越来越重要，已经提出了许多不同的方法来在风险分析模型中纳入智能对手。然而，这些方法基于一系列关于智能对手模型理想特性的隐含假设。本“观点”论文旨在通过促进对这些模型理想特性的讨论，进一步分析涉及智能对手的风险。提出并讨论了智能对手模型的四个基本必要条件：（1）尽可能准确的行为表现，（2）支持决策制定的计算可处理性，（3）明确考虑不确定性，以及（4）对模型建立信心的能力。希望这些建议的必要条件能够促进关于风险分析中智能对手建模的目标和假设的讨论。
