Fuzzy reasoning with a rete-oo rule engine

Nikolaus Wulff, Davide Sottara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Rules and rule engines play an important role in automated decision making processes like business workflows or system monitoring. Classical inference machines evaluate rules until a final "yes" or "no" decision: this crisp classification schema can turn into a deficiency when they have to deal with uncertain or inprecise knowledge. To circumvent some of these limitations we have built the "Java Expert Fuzzy Inference System" (Jefis) and implemented factory methods to deploy the Jefis library as an extension for the classical rule engine JBoss Drools. We outline the new features and give examples of uncertain formulated rules executing within the Jefis Drools extender.

Original languageEnglish (US)
Title of host publicationRule Interchange and Applications - International Symposium, RuleML 2009, Proceedings
Pages337-344
Number of pages8
DOIs
StatePublished - Dec 3 2009
Externally publishedYes
EventInternational Symposium on Rule Interchange and Applications, RuleML 2009 - Las Vegas, NV, United States
Duration: Nov 5 2009Nov 7 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5858 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Symposium on Rule Interchange and Applications, RuleML 2009
CountryUnited States
CityLas Vegas, NV
Period11/5/0911/7/09

Fingerprint

Fuzzy Reasoning
Fuzzy inference
Engine
Fuzzy Inference System
Engines
Java
Industrial plants
Decision making
Monitoring
Schema
Work Flow
Decision Making
Industry
Evaluate

Keywords

  • Fuzzy logic
  • Inference engine
  • Uncertain reasoning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Wulff, N., & Sottara, D. (2009). Fuzzy reasoning with a rete-oo rule engine. In Rule Interchange and Applications - International Symposium, RuleML 2009, Proceedings (pp. 337-344). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5858 LNCS). https://doi.org/10.1007/978-3-642-04985-9_31

Fuzzy reasoning with a rete-oo rule engine. / Wulff, Nikolaus; Sottara, Davide.

Rule Interchange and Applications - International Symposium, RuleML 2009, Proceedings. 2009. p. 337-344 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5858 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wulff, N & Sottara, D 2009, Fuzzy reasoning with a rete-oo rule engine. in Rule Interchange and Applications - International Symposium, RuleML 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5858 LNCS, pp. 337-344, International Symposium on Rule Interchange and Applications, RuleML 2009, Las Vegas, NV, United States, 11/5/09. https://doi.org/10.1007/978-3-642-04985-9_31
Wulff N, Sottara D. Fuzzy reasoning with a rete-oo rule engine. In Rule Interchange and Applications - International Symposium, RuleML 2009, Proceedings. 2009. p. 337-344. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-04985-9_31
Wulff, Nikolaus ; Sottara, Davide. / Fuzzy reasoning with a rete-oo rule engine. Rule Interchange and Applications - International Symposium, RuleML 2009, Proceedings. 2009. pp. 337-344 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{402865e1e9b240b38a01a789117fd499,
title = "Fuzzy reasoning with a rete-oo rule engine",
abstract = "Rules and rule engines play an important role in automated decision making processes like business workflows or system monitoring. Classical inference machines evaluate rules until a final {"}yes{"} or {"}no{"} decision: this crisp classification schema can turn into a deficiency when they have to deal with uncertain or inprecise knowledge. To circumvent some of these limitations we have built the {"}Java Expert Fuzzy Inference System{"} (Jefis) and implemented factory methods to deploy the Jefis library as an extension for the classical rule engine JBoss Drools. We outline the new features and give examples of uncertain formulated rules executing within the Jefis Drools extender.",
keywords = "Fuzzy logic, Inference engine, Uncertain reasoning",
author = "Nikolaus Wulff and Davide Sottara",
year = "2009",
month = "12",
day = "3",
doi = "10.1007/978-3-642-04985-9_31",
language = "English (US)",
isbn = "3642049842",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "337--344",
booktitle = "Rule Interchange and Applications - International Symposium, RuleML 2009, Proceedings",

}

TY - GEN

T1 - Fuzzy reasoning with a rete-oo rule engine

AU - Wulff, Nikolaus

AU - Sottara, Davide

PY - 2009/12/3

Y1 - 2009/12/3

N2 - Rules and rule engines play an important role in automated decision making processes like business workflows or system monitoring. Classical inference machines evaluate rules until a final "yes" or "no" decision: this crisp classification schema can turn into a deficiency when they have to deal with uncertain or inprecise knowledge. To circumvent some of these limitations we have built the "Java Expert Fuzzy Inference System" (Jefis) and implemented factory methods to deploy the Jefis library as an extension for the classical rule engine JBoss Drools. We outline the new features and give examples of uncertain formulated rules executing within the Jefis Drools extender.

AB - Rules and rule engines play an important role in automated decision making processes like business workflows or system monitoring. Classical inference machines evaluate rules until a final "yes" or "no" decision: this crisp classification schema can turn into a deficiency when they have to deal with uncertain or inprecise knowledge. To circumvent some of these limitations we have built the "Java Expert Fuzzy Inference System" (Jefis) and implemented factory methods to deploy the Jefis library as an extension for the classical rule engine JBoss Drools. We outline the new features and give examples of uncertain formulated rules executing within the Jefis Drools extender.

KW - Fuzzy logic

KW - Inference engine

KW - Uncertain reasoning

UR - http://www.scopus.com/inward/record.url?scp=70749097603&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70749097603&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-04985-9_31

DO - 10.1007/978-3-642-04985-9_31

M3 - Conference contribution

SN - 3642049842

SN - 9783642049842

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 337

EP - 344

BT - Rule Interchange and Applications - International Symposium, RuleML 2009, Proceedings

ER -