Interactive scheduling of appliance usage in the home
Interactive scheduling of appliance usage in the home
We address the problem of recommending an appliance usage schedule to the homeowner which balances between maximising total savings and maintaining sufficient user convenience. An important challenge within this problem is how to elicit the user preferences with low intrusiveness, in order to identify new schedules with high cost savings, that still lies within the user’s comfort zone. To tackle this problem we propose iDR, an interactive system for generating personalised appliance usage scheduling recommendations that maximise savings and convenience with minimal intrusiveness. In particular, our system learns when to stop interacting with the user during the preference elicitation process, in order to keep the bother cost (e.g., the amount of time the user spends, or the cognitive cost of interacting) minimal. We demonstrate through extensive empirical evaluation on real–world data that our approach improves savings by up to 35%, while maintaining a significantly lower bother cost, compared to state-of the-art benchmarks.
Truong, Ngoc Cuong
fd263fca-cd6b-48eb-b9be-30e168a51a39
Baarslag, Tim
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Ramchurn, Gopal
1d62ae2a-a498-444e-912d-a6082d3aaea3
Tran-Thanh, Long
e0666669-d34b-460e-950d-e8b139fab16c
9 July 2016
Truong, Ngoc Cuong
fd263fca-cd6b-48eb-b9be-30e168a51a39
Baarslag, Tim
a7c541d8-8141-467b-a08c-7a81cd69920e
Ramchurn, Gopal
1d62ae2a-a498-444e-912d-a6082d3aaea3
Tran-Thanh, Long
e0666669-d34b-460e-950d-e8b139fab16c
Truong, Ngoc Cuong, Baarslag, Tim, Ramchurn, Gopal and Tran-Thanh, Long
(2016)
Interactive scheduling of appliance usage in the home.
25th International Joint Conference on Artificial Intelligence (IJCAI-160, New York, United States.
09 - 15 Jul 2016.
7 pp
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
We address the problem of recommending an appliance usage schedule to the homeowner which balances between maximising total savings and maintaining sufficient user convenience. An important challenge within this problem is how to elicit the user preferences with low intrusiveness, in order to identify new schedules with high cost savings, that still lies within the user’s comfort zone. To tackle this problem we propose iDR, an interactive system for generating personalised appliance usage scheduling recommendations that maximise savings and convenience with minimal intrusiveness. In particular, our system learns when to stop interacting with the user during the preference elicitation process, in order to keep the bother cost (e.g., the amount of time the user spends, or the cognitive cost of interacting) minimal. We demonstrate through extensive empirical evaluation on real–world data that our approach improves savings by up to 35%, while maintaining a significantly lower bother cost, compared to state-of the-art benchmarks.
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truong_ijcai16.pdf
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More information
Accepted/In Press date: 5 April 2016
e-pub ahead of print date: 9 June 2016
Published date: 9 July 2016
Venue - Dates:
25th International Joint Conference on Artificial Intelligence (IJCAI-160, New York, United States, 2016-07-09 - 2016-07-15
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 396670
URI: http://eprints.soton.ac.uk/id/eprint/396670
PURE UUID: dabd3772-0ecf-4fe0-82c8-f6d6cfda49df
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Date deposited: 10 Jun 2016 13:43
Last modified: 15 Mar 2024 03:22
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