Modeling uncertainty in declarative artifact-centric process models

Research output: Contribution to conferencePaperAcademic

Abstract

Many knowledge-intensive processes are driven by business
entities about which knowledge workers make decisions and to which they
add information. Artifact-centric process models have been proposed to
represent such knowledge-intensive processes. Declarative artifact-centric
process models use business rules that dene how knowledge experts
can make progress in a process. However, in many business situations
knowledge experts have to deal with uncertainty and vagueness. Currently,
how to deal with such situations cannot be expressed in declarative
artifact-centric process models. We propose the use of fuzzy logic to
model uncertainty.We use Guard-Stage-Milestone schemas as declarative
artifact-centric process notation and we extend them with fuzzy sentries.
We explain how the resulting fuzzy GSM schemas can be evaluated by
extending an existing GSM engine with a tool for fuzzy evaluation of
rules. We evaluate fuzzy GSM schemas by applying them to an existing
fragment of regulations for handling a mortgage contract.

Workshop

Workshop2018 Artificial Intelligence for Business Process Management Workshop (AI4BPM 20018)
Abbreviated titleAI4BPM 2018
CountryAustralia
CitySydney
Period9/09/1814/09/18
Internet address

Fingerprint

Global system for mobile communications
Industry
Fuzzy logic
Engines
Uncertainty

Keywords

  • Declarative Artifact-Centric Process Models
  • Modeling Uncertainty

Cite this

Eshuis, H., & Firat, M. (2018). Modeling uncertainty in declarative artifact-centric process models. Paper presented at 2018 Artificial Intelligence for Business Process Management Workshop (AI4BPM 20018), Sydney, Australia.
Eshuis, H. ; Firat, M./ Modeling uncertainty in declarative artifact-centric process models. Paper presented at 2018 Artificial Intelligence for Business Process Management Workshop (AI4BPM 20018), Sydney, Australia.
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title = "Modeling uncertainty in declarative artifact-centric process models",
abstract = "Many knowledge-intensive processes are driven by businessentities about which knowledge workers make decisions and to which theyadd information. Artifact-centric process models have been proposed torepresent such knowledge-intensive processes. Declarative artifact-centricprocess models use business rules that dene how knowledge expertscan make progress in a process. However, in many business situationsknowledge experts have to deal with uncertainty and vagueness. Currently,how to deal with such situations cannot be expressed in declarativeartifact-centric process models. We propose the use of fuzzy logic tomodel uncertainty.We use Guard-Stage-Milestone schemas as declarativeartifact-centric process notation and we extend them with fuzzy sentries.We explain how the resulting fuzzy GSM schemas can be evaluated byextending an existing GSM engine with a tool for fuzzy evaluation ofrules. We evaluate fuzzy GSM schemas by applying them to an existingfragment of regulations for handling a mortgage contract.",
keywords = "Declarative Artifact-Centric Process Models, Modeling Uncertainty",
author = "H. Eshuis and M. Firat",
year = "2018",
language = "English",
note = "2018 Artificial Intelligence for Business Process Management Workshop (AI4BPM 20018), AI4BPM 2018 ; Conference date: 09-09-2018 Through 14-09-2018",
url = "https://sites.google.com/view/ai4bpm-2018/home",

}

Eshuis, H & Firat, M 2018, 'Modeling uncertainty in declarative artifact-centric process models' Paper presented at 2018 Artificial Intelligence for Business Process Management Workshop (AI4BPM 20018), Sydney, Australia, 9/09/18 - 14/09/18, .

Modeling uncertainty in declarative artifact-centric process models. / Eshuis, H.; Firat, M.

2018. Paper presented at 2018 Artificial Intelligence for Business Process Management Workshop (AI4BPM 20018), Sydney, Australia.

Research output: Contribution to conferencePaperAcademic

TY - CONF

T1 - Modeling uncertainty in declarative artifact-centric process models

AU - Eshuis,H.

AU - Firat,M.

PY - 2018

Y1 - 2018

N2 - Many knowledge-intensive processes are driven by businessentities about which knowledge workers make decisions and to which theyadd information. Artifact-centric process models have been proposed torepresent such knowledge-intensive processes. Declarative artifact-centricprocess models use business rules that dene how knowledge expertscan make progress in a process. However, in many business situationsknowledge experts have to deal with uncertainty and vagueness. Currently,how to deal with such situations cannot be expressed in declarativeartifact-centric process models. We propose the use of fuzzy logic tomodel uncertainty.We use Guard-Stage-Milestone schemas as declarativeartifact-centric process notation and we extend them with fuzzy sentries.We explain how the resulting fuzzy GSM schemas can be evaluated byextending an existing GSM engine with a tool for fuzzy evaluation ofrules. We evaluate fuzzy GSM schemas by applying them to an existingfragment of regulations for handling a mortgage contract.

AB - Many knowledge-intensive processes are driven by businessentities about which knowledge workers make decisions and to which theyadd information. Artifact-centric process models have been proposed torepresent such knowledge-intensive processes. Declarative artifact-centricprocess models use business rules that dene how knowledge expertscan make progress in a process. However, in many business situationsknowledge experts have to deal with uncertainty and vagueness. Currently,how to deal with such situations cannot be expressed in declarativeartifact-centric process models. We propose the use of fuzzy logic tomodel uncertainty.We use Guard-Stage-Milestone schemas as declarativeartifact-centric process notation and we extend them with fuzzy sentries.We explain how the resulting fuzzy GSM schemas can be evaluated byextending an existing GSM engine with a tool for fuzzy evaluation ofrules. We evaluate fuzzy GSM schemas by applying them to an existingfragment of regulations for handling a mortgage contract.

KW - Declarative Artifact-Centric Process Models

KW - Modeling Uncertainty

M3 - Paper

ER -

Eshuis H, Firat M. Modeling uncertainty in declarative artifact-centric process models. 2018. Paper presented at 2018 Artificial Intelligence for Business Process Management Workshop (AI4BPM 20018), Sydney, Australia.