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Decision Infrastructure for Counterinsurgency Operational Planning (DICOP)

机译:反对欲险计划计划的决策基础设施(DICOP)

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This paper describes a new Decision Infrastructure for Counterinsurgency Operational Planning (DICOP). DICOP facilitates the cognitive processes of the command team by providing a method for organizing relevant situational data, visualizing and modeling operational factors, assessing uncertainty and risk, and identifying and planning courses of action that are likely to provide the greatest utility. DICOP is organized around three main components: Mission Analysis; Mission Modeling; and Mission Planning. Mission Analysis provides a method for rapidly organizing and analyzing incoming intelligence and situational information. Mission Modeling provides a structure for constructing campaign models (lines of effort, objectives, and end states), using doctrinal templates, assessing the impact of situational factors, and associating intelligence information with the model. Mission Planning supports resource to task allocation, scheduling, and order generation. Initial positive evaluation by US Army command personnel has shown that DICOP is a powerful tool that fits the needs of the counterinsurgency planning team. Users highlighted three key cognitive features: (1) the ability to explicitly represent and manipulate operational factors in a modeling framework, (2) the ability to directly associate intelligence in support for or against those factors, and (3) numerical measures of utility and risk for different courses of action. The paper describes the DICOP cognitive rationale, its functional features, its initial evaluation, and the plans for further empirical evaluation in an operational environment.
机译:本文介绍了对反矩形运营计划(DICOP)的新决策基础设施。 DICOP通过提供组织相关的情境数据,可视化和建模运营因素的方法,促进命令团队的认知过程,评估不确定性和风险,以及识别和规划可能提供最大效用的行动课程。 Dicop围绕三个主要成分组织:使命分析;任务建模;和任务规划。任务分析提供了一种快速组织和分析传入智能和境地信息的方法。任务建模提供了构建活动模型(努力,目标和终端状态)的结构,使用教义模板,评估情境因素的影响以及将智能信息与模型相关联。使命计划支持资源到任务分配,调度和订单生成。美国陆军指挥人员的初步肯定评估表明,DICOP是一个强大的工具,符合对方尿俗计划团队的需求。用户突出显示了三个关键认知功能:(1)能够在建模框架中明确表示和操作运营因素,(2)能够直接将智能联系在支持或反对这些因素的情况下,以及(3)实用的数值措施不同行动课程的风险。本文介绍了DICOP认知理由,其功能特征,其初步评估以及在运营环境中进一步实证评估的计划。

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