Mahesar, Q, Dimitrova, V orcid.org/0000-0002-7001-0891, Magee, D et al. (1 more author) (2018) Uncertainty Management for Rule-Based Decision Support Systems. In: Proceedings of ICTAI 2017: 29th IEEE International Conference on Tools with Artificial Intelligence. ICTAI 2017: 29th IEEE International Conference on Tools with Artificial Intelligence, 06-08 Nov 2017, Boston, MA, USA. Institute of Electrical and Electronics Engineers , pp. 884-891. ISBN 978-1-5386-3877-4
Abstract
We present an uncertainty management scheme in rule-based systems for decision making in the domain of urban infrastructure. Our aim is to help end users make informed decisions. Human reasoning is prone to a certain degree of uncertainty but domain experts frequently find it difficult to quantify this precisely, and thus prefer to use qualitative (rather than quantitative) confidence levels to support their reasoning. Secondly, there is uncertainty in data when it is not currently available (missing). In order to incorporate human-like reasoning within rule-based systems we use qualitative confidence levels chosen by domain experts in urban infrastructure. We introduce a mechanism for the representation of confidence of input facts and inference rules, and for the computation of confidence in the inferred facts. We also present a mechanism for computing inferences in the presence of missing facts, and their effect on the confidence of inferred facts.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017, IEEE. This is an author produced version of a paper published in Proceedings of ICTAI 2017: 29th IEEE International Conference on Tools with Artificial Intelligence. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | uncertainty; decision support systems; reasoning |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number EPSRC EP/K021699/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 03 Nov 2017 11:43 |
Last Modified: | 11 Jul 2018 14:49 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Identification Number: | 10.1109/ICTAI.2017.00137 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:123450 |