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Decision support information integration platform for context-driven interdiction operations in counter-smuggling missions

机译:决策支持信息集成平台,用于反走私任务中的情境驱动拦截行动

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Context-driven decision making is at the top of the Navy's agenda of important concepts to be embedded in future proactive decision support systems for command decision making. There are manifold challenges associated with relaying contextual data in a timely manner to the decision maker. In the counter-smuggling domain, for example, although high value information is accessible, it is dispersed across databases and the decision making team. There are numerous research challenges in integrating this information in an efficient manner to effectively present viable courses of action to a decision making team. In this paper, we propose a decision support tool for counter-smuggling missions modeled as a stochastic control problem of dynamically managing assets to maximize the probability of detecting and interdicting maritime illicit trafficking operations. We additionally propose a method to explain the algorithm behavior to the human decision maker and provide them with interactive controls to develop “what-if” solutions or to constrain solutions to a desired path.
机译:上下文驱动的决策是海军重要议程的重中之重,这些概念将嵌入到未来的主动决策支持系统中,以进行指挥决策。及时将上下文数据传递给决策者会带来很多挑战。例如,在反走私领域,尽管可以访问高价值信息,但它们分散在数据库和决策团队中。在有效地整合这些信息以有效地向决策团队提出可行的行动方案方面,存在许多研究挑战。在本文中,我们提出了一种针对反走私任务的决策支持工具,该工具被建模为动态管理资产的随机控制问题,以最大程度地发现和阻止海上非法贩运活动的可能性。我们还提出了一种方法来向人类决策者解释算法行为,并为他们提供交互式控件,以开发“假设分析”解决方案或将解决方案约束到所需路径。

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