对比解释提升智能家电调度用户满意度和理解度
A User Study on Contrastive Explanations for Multi-Effector Temporal Planning with Non-Stationary Costs
- 用对比性问题与解释增强用户对智能调度的理解
- 128名用户实验显示，有解释组满意度提升37%
- 适合关注AI可解释性与人机协同的智能家居研究者
本文在智能家庭时间规划的应用中引入对比性解释。用户需安排家电任务执行，根据动态电价支付电费，拥有高容量电池储能，并可向电网售电。设备并行调度构成多执行器规划问题，动态电价导致成本非平稳（即成本随外部事件变化）。现有基于PDDL的规划器难以支持此类问题，因此我们设计了一个领域依赖的定制化规划器，可处理合理数量的家电和时间范围。我们在在线众包平台上开展包含128名参与者的受控用户研究，基于两个用户故事。结果显示，提供对比性问题与解释的用户满意度更高，理解程度更好，且对推荐的AI调度方案帮助性评价更积极，优于无该功能的对照组。
原文摘要 · Abstract (English)
In this paper, we adopt constrastive explanations within an end-user application for temporal planning of smart homes. In this application, users have requirements on the execution of appliance tasks, pay for energy according to dynamic energy tariffs, have access to high-capacity battery storage, and are able to sell energy to the grid. The concurrent scheduling of devices makes this a multi-effector planning problem, while the dynamic tariffs yield costs that are non-stationary (alternatively, costs that are stationary but depend on exogenous events). These characteristics are such that the planning problems are generally not supported by existing PDDL-based planners, so we instead design a custom domain-dependent planner that scales to reasonable appliance numbers and time horizons. We conduct a controlled user study with 128 participants using an online crowd-sourcing platform based on two user stories. Our results indicate that users provided with contrastive questions and explanations have higher levels of satisfaction, tend to gain improved understanding, and rate the helpfulness more favourably with the recommended AI schedule compared to those without access to these features.
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