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Abstract
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.
Original language | English |
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Title of host publication | 2024 IEEE 36th International Conference on Tools with Artificial Intelligence (ICTAI) |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 413-419 |
Number of pages | 7 |
ISBN (Electronic) | 9798331527235 |
ISBN (Print) | 9798331527242 |
DOIs | |
Publication status | Published - 28 Jan 2025 |
Event | ICTAI 2024 : 36th International Conference on Tools with Artificial Intelligence - Herndon, United States Duration: 28 Oct 2024 → 30 Oct 2024 Conference number: 2024 https://ictai.computer.org/2024/ |
Publication series
Name | International Conference on Tools with Artificial Intelligence |
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Publisher | IEEE |
ISSN (Print) | 1082-3409 |
ISSN (Electronic) | 2375-0197 |
Conference
Conference | ICTAI 2024 : 36th International Conference on Tools with Artificial Intelligence |
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Abbreviated title | ICTAI |
Country/Territory | United States |
City | Herndon |
Period | 28/10/24 → 30/10/24 |
Internet address |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- explainable AI planning
- user study
- contrastive explanations
- temporal planning
- multi-effector
- non-stationary
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Dive into the research topics of 'A User Study on Contrastive Explanations for Multi-Effector Temporal Planning with Non-Stationary Costs'. Together they form a unique fingerprint.Projects
- 1 Finished
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CHAI: Cyber Hygiene in AI enabled domestic life
Liu, W. (Principal Investigator)
1/12/20 → 28/02/24
Project: Research