JARET:用于目标回顾和时间管理的人类辅助人工智能代理

Andrew Schwabe
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引用次数: 0

摘要

许多学生没有设定目标或每周计划自己的时间(由于缺乏能力、感知困难和其他原因),导致拖延、压力和学习成绩下降。本文介绍了一种人类辅助人工智能代理的设计方法和考虑因素,该代理可以帮助学生复习和计划学习目标,将大型抽象问题简化为一组更简单的复习任务。J.A.R.E.T. (Just A Recommender Engine for Time)将自我调节学习和认知负荷理论(Cognitive Load Theory)中的关键原则运用到一个互动系统中,引导学生完成重点目标审查和任务规划,然后使用约束满足人工智能代理来组合一个旨在帮助学生实现目标的拟议日历时间表。人工智能代理使用硬约束和软约束以及设计的价值函数,并搜索遵循约束的最佳匹配,同时尝试满足学生的偏好。结果表明,当约束和偏好合理且没有过度限制时,设计能够可靠地构建推荐解决方案。
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JARET: A Human Assistive A.I. Agent for Goal Review and Time Management
Many students do not set goals or plan their time weekly (due to lack of ability, perceived difficulty, and other reasons) resulting in procrastination, stress, and lower academic performance. This paper presents the design methodology and considerations for a human assistive AI agent that helps students review and plan for study goals, reducing a large abstract problem into a set of simpler review tasks.  J.A.R.E.T. (Just A Recommender Engine for Time) uses key principles from Self-Regulated Learning and Cognitive Load Theory in an interactive system that guides students through focused goal review and planning tasks, then uses a constraint satisfaction AI agent to assemble a proposed calendar schedule designed to help achieve the student’s goals.  The AI agent uses hard and soft constraints with a value function designed and searches for a best fit that follows constraints while trying to also fit student preferences.  Results show that the design is able to reliably build recommended solutions when constraints and preferences are reasonable and not overly restrictive.
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