An extensive study of security games with strategic informants

贝叶斯博弈 斯塔克伯格竞赛 计算机科学 计算机安全 运筹学 博弈论 阻截 重复博弈 微观经济学 经济 数学 工程类 航空航天工程
作者
Weiran Shen,Minbiao Han,W P Chen,Taoan Huang,Rohit Singh,Haifeng Xu,Fei Fang
出处
期刊:Artificial Intelligence [Elsevier]
卷期号:334: 104162-104162
标识
DOI:10.1016/j.artint.2024.104162
摘要

Over the past years, game-theoretic modeling for security and public safety issues (also known as security games) 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 – strategic informants 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. For situations with a single informant, we capture the problem as a 3-player extensive-form game and develop a novel solution concept, Strong Stackelberg-perfect Bayesian equilibrium, for the game. To find an optimal defender strategy, we establish that though the informant can have infinitely many types in general, there always exists an optimal defense plan using only a linear number of patrol strategies; this succinct characterization then enables us to efficiently solve the game via linear programming. For situations with multiple informants, we show that there is also an optimal defense plan with only a linear number of patrol strategies that admits a simple structure based on plurality voting among multiple informants. Finally, we conduct extensive experiments to study the effect of the strategic informants and demonstrate the efficiency of our algorithm. Our experiments show that the existence of such informants significantly increases the defender's utility. Even though the informants exhibit strategic behaviors, the information they supply holds great value as defensive resources. Compared to existing works, our study leads to a deeper understanding on the role of informants in such defender-attacker interactions.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
monicaaaa完成签到,获得积分10
刚刚
1秒前
大个应助清秀的飞风采纳,获得30
2秒前
2秒前
源孤律醒完成签到 ,获得积分10
4秒前
徐畅完成签到 ,获得积分10
5秒前
5秒前
wlscj应助科研通管家采纳,获得20
5秒前
zhonglv7应助科研通管家采纳,获得10
5秒前
科研通AI6应助科研通管家采纳,获得10
5秒前
wanci应助科研通管家采纳,获得10
5秒前
yiyitx应助科研通管家采纳,获得10
5秒前
科研通AI6应助科研通管家采纳,获得10
5秒前
小蘑菇应助科研通管家采纳,获得10
5秒前
梁林林完成签到,获得积分10
5秒前
科研通AI6应助科研通管家采纳,获得10
5秒前
FashionBoy应助科研通管家采纳,获得10
5秒前
科研通AI6应助科研通管家采纳,获得10
5秒前
大模型应助科研通管家采纳,获得10
5秒前
Jasper应助科研通管家采纳,获得10
5秒前
5秒前
852应助科研通管家采纳,获得10
5秒前
在水一方应助科研通管家采纳,获得10
6秒前
6秒前
zhonglv7应助科研通管家采纳,获得10
6秒前
wanci应助科研通管家采纳,获得10
6秒前
mengyuhuan完成签到,获得积分0
6秒前
领导范儿应助牛牛采纳,获得10
6秒前
yiyitx应助科研通管家采纳,获得20
6秒前
852应助科研通管家采纳,获得10
6秒前
上官若男应助科研通管家采纳,获得10
6秒前
闪闪小帆完成签到,获得积分10
6秒前
情怀应助科研通管家采纳,获得10
6秒前
科目三应助科研通管家采纳,获得10
6秒前
6秒前
完美世界应助科研通管家采纳,获得10
6秒前
6秒前
zhenghang完成签到,获得积分10
6秒前
7秒前
7秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Petrucci's General Chemistry: Principles and Modern Applications, 12th edition 600
FUNDAMENTAL STUDY OF ADAPTIVE CONTROL SYSTEMS 500
微纳米加工技术及其应用 500
Constitutional and Administrative Law 500
PARLOC2001: The update of loss containment data for offshore pipelines 500
Vertebrate Palaeontology, 5th Edition 420
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5296623
求助须知:如何正确求助?哪些是违规求助? 4445778
关于积分的说明 13837294
捐赠科研通 4330749
什么是DOI,文献DOI怎么找? 2377237
邀请新用户注册赠送积分活动 1372556
关于科研通互助平台的介绍 1337990