在公共交通系统中玩多目标抽查游戏

SHCIS '17 Pub Date : 2017-06-19 DOI:10.1145/3099012.3099019
Ali Alshawish, Mohamed Amine Abid, S. Rass, H. Meer
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引用次数: 4

摘要

公共交通系统是任何国家重要基础设施的重要组成部分。因此,他们的服务的连续性被认为是重要的,是各国的高度优先事项。对恐怖主义、刑事犯罪和商业收入损失等风险的担忧,要求加强这些系统的态势感知能力。然而,诸如对乘客进行随机巡逻或定期抽查以防止或制止潜在违规行为的做法,受到可用资源(例如保安人员或检票员)的数量以及潜在对手(例如罪犯或逃票者)预测或观察检票员存在模式的能力的严格限制。将这些竞争实体(检查员/安全官员和罪犯/逃票者)之间的相互作用纳入博弈论模型将使相关系统操作员能够1)找到最优的成本效益(或多目标)人力资源分配或抽查计划,2)捕获和处理由于信息不完善而产生的不确定性,3)整合异构性质的测量(例如统计数据、专家意见或模拟结果)。这项工作应用了一个博弈论模型,该模型使用随机的概率分布值回报,允许进行具有不同行动结果的抽查游戏,并避免由于将多个测量值组合到一个代表(例如平均值)中而导致的信息丢失。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Playing a Multi-objective Spot-checking Game in Public Transportation Systems
Public transportation systems represent an essential sector of any nation's critical infrastructure. Hence, continuity of their services is deemed important and with a high priority to the nations. Concerns over risks like terrorism, criminal offenses, and business revenue loss impose the need for enhancing situation awareness in these systems. However, practices, such as conducting random patrols or regular spot-checks on passengers to prevent or deter potential violations, are strictly limited by the number of available resources (e.g. security staff or fare inspectors) and by the ability of potential opponents (e.g. criminals, or fare evaders) to predict or observe the inspectors' presence patterns. Casting the interactions between these competitive entities (inspectors/security officials and criminals/fare dodgers) into a game-theoretic model will enable involved system operators to 1) find optimal cost-effective (or multi-goal) human resource allocation or spot-check schedules, 2) capture and treat uncertainty due to imperfectness of information, 3) integrate measurements from heterogeneous natures (e.g. statistics, expert opinions, or simulation results). This work applies a game-theoretical model that uses random probability-distribution-valued payoffs to allow playing spot-checking games with diverging actions' outcomes as well as avoiding information loss due to combining several measurements into one representative (e.g. average).
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