Cognitive Shadow: capturing judgement policies for real-time decision support

认知影子：捕捉判断策略以提供实时决策支持

• 批准号: 518400-2017
• 负责人: Tremblay, Sébastien
• 金额: $ 4.18万
• 依托单位: Université Laval
• 依托单位国家: 加拿大
• 项目类别: Department of National Defence / NSERC Research Partnership
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=697208
• 关键词: Cognitive; Shadow; capturing; judgement; policies

Formally capturing expert knowledge is a major challenge in the field of decision support. Policy capturing is a judgment analysis method that infers a decision policy based on past examples. A "judgmental bootstrapping" effect can be observed when a model actually outperforms the human decision maker on which the model was based (typically because the model is not prone to fatigue or distraction). A prototype policy capturing tool called the Cognitive Shadow has been developed to automatically learn an operator's decision pattern and provide warnings in real-time when a mismatch is detected between the user's decision and the inferred decision policy. This project aims at investigating critical human factors and cognitive engineering issues for implementing the Cognitive Shadow capability in the context of naval air defence. The specific objectives are to 1) assess factors influencing operator trust in the cognitive assistant, 2) assess impacts on workload, behavior and performance measures, and 3) understand the different impacts of two possible modes of operation: a shadowing mode where the operator receives an alert only when a mismatch with the decision model is detected, versus a recommendation mode where the operator receives information about the model's expected decision. A series of human-in-the-loop experiments will be performed in two phases in order to systematically investigate these issues. In Phase 1 the Simulated Combat Control System testbed is used as a functional simulation of naval air defence practiced aboard the Canadian Navy's Halifax class frigates. Phase 1 will involve two laboratory experiments involving implementations of the Cognitive Shadow hypothesized to differentially impact workload, trust, performance and competency preservation. Phase 2 will involve using the Cognitive Shadow with domain experts in the context of a real-world combat management system. This project will help Thales Research and Technology Canada take a leap forward in maturing the new Cognitive Shadow technology, and Defence Research and Development Canada in leveraging the technological advances for the Royal Canadian Navy.

形式化地获取专家知识是决策支持领域的一个主要挑战。策略捕获是一种判断分析方法，它根据过去的例子推断决策策略。当一个模型实际上优于该模型所基于的人类决策者时，可以观察到“判断自举”效应（通常是因为该模型不容易疲劳或分心）。一个原型的策略捕获工具，称为认知阴影已经开发自动学习运营商的决策模式，并提供实时警告时，检测到用户的决定和推断的决策策略之间的不匹配。该项目旨在调查在海军防空背景下实施认知阴影能力的关键人为因素和认知工程问题。具体目标是：1）评估影响操作员对认知助手信任的因素，2）评估对工作负荷的影响， 行为和性能测量，以及3）理解两种可能的操作模式的不同影响：阴影模式，其中操作员仅在检测到与决策模型不匹配时接收警报，而推荐模式，其中操作员接收关于模型的预期决策的信息。为了系统地研究这些问题，将分两个阶段进行一系列人在回路中的实验。在第一阶段，模拟战斗控制系统试验台被用作加拿大海军哈利法克斯级护卫舰上练习的海军防空的功能模拟。第一阶段将涉及两个实验室实验，涉及实施认知阴影假设差异影响工作量，信任，性能和能力保护。第二阶段将涉及在现实世界的战斗管理系统中与领域专家一起使用认知阴影。该项目将帮助加拿大泰雷兹研究和技术公司在成熟新的认知阴影方面取得飞跃 技术，加拿大国防研究与发展部为皇家加拿大海军利用技术进步。