Uncertainty Management for Rule-based Decision Support Systems

Quratul Ain Mahesar, Vania Dimitrova, Derek Magee, Anthony Cohn

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - 2017 International Conference on Tools with Artificial Intelligence
Subtitle of host publication(ICTAI 2017)
PublisherIEEE Computer Society
Pages884-891
Number of pages8
ISBN (Electronic)9781538638767
ISBN (Print)9781538638774
DOIs
Publication statusPublished - 7 Jun 2018
Externally publishedYes
Event29th IEEE International Conference on Tools with Artificial Intelligence - Boston, United States
Duration: 6 Nov 20178 Nov 2017
Conference number: 29

Publication series

NameProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
ISSN (Print)1082-3409
ISSN (Electronic)2375-0197

Conference

Conference29th IEEE International Conference on Tools with Artificial Intelligence
Abbreviated titleICTAI 2017
CountryUnited States
CityBoston
Period6/11/178/11/17

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