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An extensive study of security games with strategic informants
Artificial Intelligence ( IF 5.1 ) Pub Date : 2024-06-12 , DOI: 10.1016/j.artint.2024.104162 Weiran Shen , Minbiao Han , Weizhe Chen , Taoan Huang , Rohit Singh , Haifeng Xu , Fei Fang
Artificial Intelligence ( IF 5.1 ) Pub Date : 2024-06-12 , DOI: 10.1016/j.artint.2024.104162 Weiran Shen , Minbiao Han , Weizhe Chen , Taoan Huang , Rohit Singh , Haifeng Xu , Fei Fang
Over the past years, game-theoretic modeling for security and public safety issues (also known as ) have attracted intensive research attention and have been successfully deployed in many real-world applications for fighting, e.g., illegal poaching, fishing and urban crimes. However, few existing works consider how information from local communities would affect the structure of these games. In this paper, we systematically investigate how a new type of players – who are from local communities and may observe and report upcoming attacks – affects the classic defender-attacker security interactions. Characterized by a private type, each informant has a utility structure that drives their strategic behaviors.
中文翻译:
对战略线人安全博弈的广泛研究
在过去的几年里,安全和公共安全问题的博弈论模型(也称为 )引起了广泛的研究关注,并已成功应用于许多现实世界的打击应用中,例如非法偷猎、捕鱼和城市犯罪。然而,现有的工作很少考虑来自当地社区的信息将如何影响这些游戏的结构。在本文中,我们系统地研究了一种新型参与者——来自当地社区并可能观察和报告即将发生的攻击——如何影响经典的防御者-攻击者安全交互。以私人类型为特征,每个线人都有一个驱动其战略行为的效用结构。
更新日期:2024-06-12
中文翻译:
对战略线人安全博弈的广泛研究
在过去的几年里,安全和公共安全问题的博弈论模型(也称为 )引起了广泛的研究关注,并已成功应用于许多现实世界的打击应用中,例如非法偷猎、捕鱼和城市犯罪。然而,现有的工作很少考虑来自当地社区的信息将如何影响这些游戏的结构。在本文中,我们系统地研究了一种新型参与者——来自当地社区并可能观察和报告即将发生的攻击——如何影响经典的防御者-攻击者安全交互。以私人类型为特征,每个线人都有一个驱动其战略行为的效用结构。