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Tariff agent: interacting with a future smart energy system at home

Alan, Alper T.; Costanza, Enrico; Ramchurn, Sarvapali D.; Fischer, Joel E.; Rodden, Tom; Jennings, Nicholas R.

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Authors

Alper T. Alan

Enrico Costanza

Sarvapali D. Ramchurn

Nicholas R. Jennings



Abstract

Smart systems are becoming increasingly ubiquitous and consequently transforming our lives. The level of system autonomy plays a vital role in the development of smart systems as it profoundly affects how people and these systems interact with each other. However, to date, there are very few studies on human interaction with such systems. This paper presents findings from two field studies where two different prototypes for automating energy tariff-switching were developed and evaluated in the wild. Both prototypes offer flexible autonomy by which users can shift the system's level of autonomy among three options: suggestion-only, semi-autonomy, and full autonomy, whenever they like. Our findings based on thematic analysis show that flexible autonomy is a promising way to sustain users' engagement with smart systems, despite their occasional mistakes. The findings also suggest that users take responsibility for the undesired outcomes of automated actions when delegation of autonomy can be adjusted flexibly.

Citation

Alan, A. T., Costanza, E., Ramchurn, S. D., Fischer, J. E., Rodden, T., & Jennings, N. R. (2016). Tariff agent: interacting with a future smart energy system at home. ACM Transactions on Computer-Human Interaction, 23(4), https://doi.org/10.1145/2943770

Journal Article Type Article
Acceptance Date Aug 1, 2016
Publication Date Aug 1, 2016
Deposit Date Sep 22, 2016
Publicly Available Date Sep 22, 2016
Journal ACM Transactions on Computer-Human Interaction
Print ISSN 1073-0516
Electronic ISSN 1557-7325
Publisher Association for Computing Machinery (ACM)
Peer Reviewed Peer Reviewed
Volume 23
Issue 4
DOI https://doi.org/10.1145/2943770
Keywords Interactive intelligent systems, human–agent interaction, flexible autonomy, smart grid, field study, internet of things
Public URL https://nottingham-repository.worktribe.com/output/797109
Publisher URL http://dl.acm.org/citation.cfm?doid=2983309.2943770
Additional Information ©ACM, 2016. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Computer-Human Interaction (TOCHI), Vol. 23, Issue 4, (August 2016) http://doi.acm.org/10.1145/2943770
Contract Date Sep 22, 2016

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