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Oct, 2015
安全博弈中对手行为的学习——PAC模型视角
Learning Adversary Behavior in Security Games: A PAC Model Perspective
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Arunesh Sinha, Debarun Kar, Milind Tambe
TL;DR
本研究使用PAC模型，直接学习对手响应功能，通过实验验证了新的对手建模方法，在提高对手模型准确性时，探讨了实际需要的数据量，提供了最佳防御策略的条件。
Abstract
Recent applications of
stackelberg security games
(SSG), from green crime to urban crime, have employed
machine learning
tools to learn and predict adversary behavior using available data about defender-adversary
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