Process Mining of a Multi-agent Business Simulator

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19520%2F18%3A00011052" target="_blank" >RIV/47813059:19520/18:00011052 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/article/10.1007/s10588-018-9268-6" target="_blank" >https://link.springer.com/article/10.1007/s10588-018-9268-6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10588-018-9268-6" target="_blank" >10.1007/s10588-018-9268-6</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Process Mining of a Multi-agent Business Simulator

Popis výsledku v původním jazyce

A multi-agent system is a useful modelling architecture in business process modelling in the sense that we can naturally implement participants in a real company with software agents. However, analysing and interpreting the simulation results of multi-agent models tends to be difficult due to the inherent complexity of the models. In this regard, another discipline - process mining - is useful for such purposes because it has demonstrated its usefulness in analysing real processes. In this article, our aim is to combine these two disciplines for exploitation in business process modelling and simulation; we extend a multi-agent-based business simulator named MAREA (Multi-Agent system with Resource-Event-Agent ontology) to be able to be analysed by means of process mining techniques. To this end, we formalise the abstract multi-agent architecture of MAREA and establish its relationship to process mining by defining how execution of a multi-agent system can be recorded as an event log, wh ich is later analysed by process mining techniques. Based on this definition, we implement functionality to extract event logs from simulation runs in MAREA. For demonstration, we implement a model of a generic trading company in MAREA and perform process structure verification and social network analyses by means of process mining techniques.

Název v anglickém jazyce

Process Mining of a Multi-agent Business Simulator

Popis výsledku anglicky

A multi-agent system is a useful modelling architecture in business process modelling in the sense that we can naturally implement participants in a real company with software agents. However, analysing and interpreting the simulation results of multi-agent models tends to be difficult due to the inherent complexity of the models. In this regard, another discipline - process mining - is useful for such purposes because it has demonstrated its usefulness in analysing real processes. In this article, our aim is to combine these two disciplines for exploitation in business process modelling and simulation; we extend a multi-agent-based business simulator named MAREA (Multi-Agent system with Resource-Event-Agent ontology) to be able to be analysed by means of process mining techniques. To this end, we formalise the abstract multi-agent architecture of MAREA and establish its relationship to process mining by defining how execution of a multi-agent system can be recorded as an event log, wh ich is later analysed by process mining techniques. Based on this definition, we implement functionality to extract event logs from simulation runs in MAREA. For demonstration, we implement a model of a generic trading company in MAREA and perform process structure verification and social network analyses by means of process mining techniques.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10200 - Computer and information sciences

Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Computational and Mathematical Organization Theory

ISSN

1381-298X

e-ISSN

—

Svazek periodika

24

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

32

Strana od-do

500-531

Kód UT WoS článku

000449967700003

EID výsledku v databázi Scopus

2-s2.0-85044952426