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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
| Workshop | 2018 Artificial Intelligence for Business Process Management Workshop (AI4BPM 20018) |
|---|---|
| Verkorte titel | AI4BPM 2018 |
| Land | Australië |
| Stad | Sydney |
| Periode | 9/09/18 → 14/09/18 |
| Internet adres |
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Modeling uncertainty in declarative artifact-centric process models. / Eshuis, H.; Firat, M.
2018. Paper gepresenteerd op 2018 Artificial Intelligence for Business Process Management Workshop (AI4BPM 20018), Sydney, Australië.Onderzoeksoutput: Bijdrage aan congres › Paper › Academic
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 -