Continuous Search and Patrolling on Networks
Continuous Search and Patrolling on Networks
批准号:
1935826
负责人:
Thomas Lidbetter
金额:
$27.66万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2023-08-31
中文摘要
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英文摘要
This award will contribute to securing the national defense by modeling and solving search and patrolling problems on networks. The project will address how to optimally patrol an airport or shopping mall to minimize the risk of a terrorist attack, how to patrol a border to guard against infiltration, or how to optimally search for an improvised explosive device or lost hiker. A major challenge of modeling such problems is that intelligent adversaries may have the capability to view current search or patrolling policies and exploit their weaknesses. This award supports an improved understanding of the strategic nature of search and patrolling problems, so that better policies can be employed to improve public safety and security. It will also address the need to understand how search and patrolling policies may be constrained by the topology of the environment. This award will support the participation of a talented graduate student in this research, and the PI will integrate the results of the research into a graduate level course in game theory.This research models search and patrolling problems on a network in continuous time and space, rather than the approach taken by most previous work of applying finite methods to a discretized search space. The project will consider the problems of finding (i) a patrol of a network that minimizes the probability of a successful attack or infiltration by an intelligent adversary and (ii) a time-minimal search for a target hidden on a network according to either a known or unknown probability distribution. A game theoretic framework will be used to deal with adversaries and unknown probability distributions, whilst a "one-sided" approach will be used in the case of known probability distributions. The research will exploit graph theoretical properties of networks to produce optimal or near-optimal policies based on an understanding of the structure of the networks, rather than using black box algorithms.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(6)
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科研奖励(0)
会议论文
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Search and Delivery Man Problems: When are depth-first paths optimal?
搜索和送货员问题:深度优先路径何时是最佳的?
DOI:
10.1016/j.ejor.2020.02.026
发表时间:
2020
期刊:
European Journal of Operational Research
影响因子:
6.4
作者:
[Alpern, Steve, Lidbetter, Thomas]
通讯作者:
Lidbetter, Thomas
Optimal pure strategies for a discrete search game
离散搜索博弈的最优纯策略
DOI:
10.1016/j.ejor.2023.08.041
发表时间:
2024
期刊:
European Journal of Operational Research
影响因子:
6.4
作者:
[Bui, Thuy, Lidbetter, Thomas, Lin, Kyle Y.]
通讯作者:
Lin, Kyle Y.
Competitive search in a network
网络中的竞争性搜索
DOI:
10.1016/j.ejor.2020.04.003
发表时间:
2020
期刊:
European Journal of Operational Research
影响因子:
6.4
作者:
[Angelopoulos, Spyros, Lidbetter, Thomas]
通讯作者:
Lidbetter, Thomas
DOI:
10.1016/j.ejor.2023.05.033
发表时间:
2023
期刊:
European Journal of Operational Research
影响因子:
6.4
作者:
[Bui, Thuy, Lidbetter, Thomas]
通讯作者:
Lidbetter, Thomas
Continuous Patrolling Games
连续巡逻游戏
DOI:
10.1287/opre.2022.2346
发表时间:
2022
期刊:
Operations Research
影响因子:
2.7
作者:
[Alpern, Steve, Bui, Thuy, Lidbetter, Thomas, Papadaki, Katerina]
通讯作者:
Papadaki, Katerina
RI: Small: Collaborative Research: Minimum-Cost Strategies for Sequential Search and Evaluation
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批准号:1909446
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项目类别:Standard Grant
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资助金额:$14.18万
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财政年份:2019
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负责人:Thomas Lidbetter
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依托单位:
海外基金