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Smart homes are powered by increasingly advanced AI, yet are controlled by, and affect, non-experts. These non-expert home users are an under-represented stakeholder in the explainable AI (XAI) literature. In this paper we facilitate future XAI research by introducing a family of smart home applications serving as a testbed to evaluate XAI with non-experts. The testbed is a hybrid-AI system spanning several AI disciplines, including machine learning and AI planning. Applications include a smart home battery and smart thermostatic radiator valve (TRV). End-user functionality is representative of leading commercial products and relevant research applications. The testbed is based on a flexible software architecture and web-based user interface, supports a range of AI tools in a modular fashion, and can be easily deployed using inexpensive consumer hardware.
|Title of host publication||Proceedings of the 14th International Conference on Agents and Artificial Intelligence (ICAART'22)|
|Editors||Ana Paula Rocha, Luc Steels, Jaap van den Herik|
|Publication status||Published - 3 Feb 2022|
|Event||ICAART 2022: 14th International Conference on Agents and Artificial Intelligence - Online|
Duration: 3 Feb 2022 → 5 Feb 2022
Conference number: 14
|Period||3/02/22 → 5/02/22|
- Explainable AI (XAI)
- Explainable Machine Learning
- Explainable AI Planning (XAIP)
- Smart Homes
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