Control Loop Model of Virtual Company in BPM Simulation

Šperka, Roman; Spišák, Marek; Slaninová, Kateřina; Martinovič, Jan; Dráždilová, Pavla

doi:10.1007/978-3-642-32922-7_53

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…Their model extracts knowledge from an existing database through simulation. Authors of [37] analyzed agent-based simulation outputs through process mining methods. In [38] an approach was presented to improve business process models based on process mining and agent-based simulation.…”

Section: Beyond the State-of-the-artmentioning

confidence: 99%

An Agent-Based Process Mining Architecture for Emergent Behavior Analysis

Bemthuis

Koot

Mes

et al. 2019

2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW)

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Information systems leave a traceable digital footprint whenever an action is executed. Business process modelers capture these digital traces to understand the behavior of a system, and to extract actual run-time models of those business processes. Despite the omnipresence of such traces, most organizations face substantial differences between the process specifications and the actual run-time behavior. Analyzing and implementing the results of systems that model business processes tend, however, to be difficult due to the inherent complexity of the models. Moreover, the observed reality in the form of lower-level real-time events, as recorded in event logs, is seldom solely explainable by higher-level process models. In this paper, we propose an architecture to model systemwide behavior by combining process mining with a multi-agent system. Digital traces, in the form of event logs, are used to iteratively mine process models from which agents can learn. The approach is initially applied to a case study of a simplified job-shop factory in which automated guided vehicles (AGVs) carry out transportation tasks. Numerical experiments show that the workflow of a process mining model can be used to enhance the agent-based system, particularly, in analyzing bottlenecks and improving decision-making.

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Section: Beyond the State-of-the-artmentioning

confidence: 99%

An Agent-Based Process Mining Architecture for Emergent Behavior Analysis

Bemthuis

Koot

Mes

et al. 2019

2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW)

View full text Add to dashboard Cite

show abstract

“…In this article, we explore the application of process mining techniques to assess the face validity of agent-based simulation models. Process mining has demonstrated its utility in the domain of agent-based simulation modeling, including model verification and performance analysis [5,9,35]. These techniques can also be used to analyze various properties, including agent behavior [14,37].…”

Section: Introductionmentioning

confidence: 99%

Using Process Mining for Face Validity Assessment in Agent-Based Simulation Models: An Exploratory Case Study

Bemthuis,

Govers,

Lazarova-Molnar

2023

Lecture Notes in Computer Science

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In the field of simulation, the key objective of a system designer is to develop a model that performs a specific task and accurately represents real-world systems or processes. A valid simulation model allows for a better understanding of the system's behavior and improved decision-making in the real world. Face validity is a subjective measure that assesses the extent to which a simulation model and its outcomes appear reasonable to an expert based on a superficial examination of the simulator's realism. Process mining techniques, which are novel datadriven methods for obtaining real-life insights into processes based on event logs, show promise when combined with effective visualization techniques. These techniques can augment the face validity assessment of simulation models in reflecting real-life behavior and play a key role in supporting humans conducting such assessments. In this paper, we present an approach that utilizes process mining techniques to assess the face validity of agent-based simulation models. To illustrate our approach, we use the Schelling model of segregation. We demonstrate how graphical representation, immersive assessment, and sensitivity analysis can be used to assess face validity based on event logs produced by the simulation model. Our study shows that process mining in combination with visualization can strongly support humans in assessing face validity of agent-based simulation models.

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Microeconomic Demand Functions Implementation in Java Experiments

Šperka

Spišák

2014

Advances in Intelligent Systems and Computing

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Control Loop Model of Virtual Company in BPM Simulation

Cited by 6 publications

References 9 publications

An Agent-Based Process Mining Architecture for Emergent Behavior Analysis

An Agent-Based Process Mining Architecture for Emergent Behavior Analysis

Using Process Mining for Face Validity Assessment in Agent-Based Simulation Models: An Exploratory Case Study

Microeconomic Demand Functions Implementation in Java Experiments

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