情境驱动的前瞻性决策支持:挑战与应用

Manisha Mishra, D. Sidoti, G. V. Avvari, Pujitha Mannaru, D. F. M. Ayala, K. Pattipati
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引用次数: 1

摘要

在高度动态、不对称和不可预测的任务环境中,快速任务规划/重新规划和执行是具有挑战性的,因为它需要一个前瞻性的决策支持(PDS)系统,该系统可以预测和适应/适应任务的变化。现有的决策支持系统充斥着过多的数据和不足的信息,导致决策者的认知超载,从而增加了任务失败的概率。为了克服信息过载的问题,必须在正确的任务背景下,在正确的时间为正确的目的,将正确的数据/信息/知识从正确的来源交付给正确的DM (6R)。在这里,我们将上下文定义为由任务目标、环境、资产、威胁/任务和dm的认知状态组成的多维演变特征空间。在本文中,我们提出了一个PDS框架:i)定义与任务上下文相关的动态集成知识;Ii)发现任务环境的变化;Iii)诊断和预测任务背景,以进行“假设”分析;iv)在考虑决策专员的工作量、时间压力、风险倾向和专业知识的情况下,提供相关的行动建议。讨论了PDS框架的两个说明性应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Context-Driven Proactive Decision Support: Challenges and Applications
Rapid mission planning/re-planning and execution in a highly dynamic, asymmetric, and unpredictable mission environment is challenging, as it requires a proactive decision sup- port (PDS) system that is anticipative and adaptive/adaptable to changes in the mission. The existing decision support sys- tems are inundated with too much data and not enough information, resulting in cognitive overloading of decision mak- ers (DMs), thereby increasing the probability of mission failure. In order to overcome the issue of information overload, it is imperative to deliver the right data/information/knowledge from the right sources in the right mission context to the right DM at the right time for the right purpose (6R). Here, we define context as a multi-dimensional evolving feature space consisting of mission goals, environment, assets, threats/tasks and cognitive state of the DMs. In this paper, we propose a PDS framework for: i) defining dynamically integrated knowledge that is relevant to the mission context; ii) detect- ing changes in mission context; iii) diagnosing and predicting mission context to develop “what-if” analysis; and iv) provid- ing relevant courses of action recommendations , while considering the DM’s workload, time pressure, risk propensity and expertise. Two illustrative applications of PDS framework are discussed.
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