A new belief rule base knowledge representation scheme and inference methodology using the evidential reasoning rule for evidence combination. (1st June 2016)
- Record Type:
- Journal Article
- Title:
- A new belief rule base knowledge representation scheme and inference methodology using the evidential reasoning rule for evidence combination. (1st June 2016)
- Main Title:
- A new belief rule base knowledge representation scheme and inference methodology using the evidential reasoning rule for evidence combination
- Authors:
- AbuDahab, Khalil
Xu, Dong-ling
Chen, Yu-wang - Abstract:
- Highlights: Generalised belief rules are introduced as an extension of traditional rules. A knowledge representation scheme based on generalised belief rules is presented. An inference methodology using the evidential reasoning approach is proposed. Abstract: In this paper, we extend the original belief rule-base inference methodology using the evidential reasoning approach by i) introducing generalised belief rules as knowledge representation scheme, and ii) using the evidential reasoning rule for evidence combination in the rule-base inference methodology instead of the evidential reasoning approach. The result is a new rule-base inference methodology which is able to handle a combination of various types of uncertainty. Generalised belief rules are an extension of traditional rules where each consequent of a generalised belief rule is a belief distribution defined on the power set of propositions, or possible outcomes, that are assumed to be collectively exhaustive and mutually exclusive. This novel extension allows any combination of certain, uncertain, interval, partial or incomplete judgements to be represented as rule-based knowledge. It is shown that traditional IF-THEN rules, probabilistic IF-THEN rules, and interval rules are all special cases of the new generalised belief rules. The rule-base inference methodology has been updated to enable inference within generalised belief rule bases. The evidential reasoning rule for evidence combination is used for theHighlights: Generalised belief rules are introduced as an extension of traditional rules. A knowledge representation scheme based on generalised belief rules is presented. An inference methodology using the evidential reasoning approach is proposed. Abstract: In this paper, we extend the original belief rule-base inference methodology using the evidential reasoning approach by i) introducing generalised belief rules as knowledge representation scheme, and ii) using the evidential reasoning rule for evidence combination in the rule-base inference methodology instead of the evidential reasoning approach. The result is a new rule-base inference methodology which is able to handle a combination of various types of uncertainty. Generalised belief rules are an extension of traditional rules where each consequent of a generalised belief rule is a belief distribution defined on the power set of propositions, or possible outcomes, that are assumed to be collectively exhaustive and mutually exclusive. This novel extension allows any combination of certain, uncertain, interval, partial or incomplete judgements to be represented as rule-based knowledge. It is shown that traditional IF-THEN rules, probabilistic IF-THEN rules, and interval rules are all special cases of the new generalised belief rules. The rule-base inference methodology has been updated to enable inference within generalised belief rule bases. The evidential reasoning rule for evidence combination is used for the aggregation of belief distributions of rule consequents. … (more)
- Is Part Of:
- Expert systems with applications. Volume 51(2016)
- Journal:
- Expert systems with applications
- Issue:
- Volume 51(2016)
- Issue Display:
- Volume 51, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 51
- Issue:
- 2016
- Issue Sort Value:
- 2016-0051-2016-0000
- Page Start:
- 218
- Page End:
- 230
- Publication Date:
- 2016-06-01
- Subjects:
- Belief rule base -- Uncertain rules -- Uncertainty modelling -- Local ignorance -- Global ignorance -- Rule-based systems -- Inference mechanisms -- Evidential reasoning rule for evidence combination
Expert systems (Computer science) -- Periodicals
Systèmes experts (Informatique) -- Périodiques
Electronic journals
006.33 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09574174 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.eswa.2015.12.013 ↗
- Languages:
- English
- ISSNs:
- 0957-4174
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3842.004220
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 805.xml