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Frame Consistency in Multi-Attribute Risk Preference Decisions

机译:多属性风险偏好决策中的框架一致性

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Resource allocation under risk and uncertainty is a complex problem, specifically when making course of action planning decisions on the battlefield. Previous research in this domain has demonstrated the performance impact of visualization aids, feedback, practice, information frame, and time pressure. However, the focus of prior research has been on how to help operators determine where to optimally place a single asset. The current research addressed the same domain, but with the multi-attribute decision of how to best allocate a suite of robotic assets across the battlefield. We explored the impact of information frame and time pressure on decision performance and situation awareness, but further manipulated whether the information frame of decision criteria were forced to a single consistent frame or allowed to vary according to which term was intuitive, regardless of frame. We found both faster response times and more accurate responses within consistently-framed displays over mixed-frame displays. In addition, response time varied less in the consistently-framed displays than the mixed-frame displays.
机译:在风险和不确定性下的资源分配是一个复杂的问题,尤其是在战场上制定行动计划时。该领域的先前研究已经证明了可视化辅助工具,反馈,实践,信息框架和时间压力对性能的影响。但是,先前研究的重点是如何帮助运营商确定最佳放置单个资产的位置。当前的研究针对同一领域,但具有如何在战场上最佳分配一组机器人资产的多属性决策。我们探讨了信息框架和时间压力对决策绩效和态势感知的影响,但进一步操纵了决策标准的信息框架是否被强制为一个一致的框架,或者是否根据直观的术语而变化,而与框架无关。我们发现一致帧显示的响应时间比混合帧显示的响应时间更快,响应也更准确。另外,一致帧显示的响应时间变化比混合帧显示的变化小。

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