Activities per year
Traditional modeling approaches, based on predefined business logic, offer little support for today’s complex environments. In this paper, we propose a conceptual agent-based simulation framework to help not only discover complex business processes but also to analyze and learn from emergent behavior arising in cyber-physical systems. Techniques originating from agent-based modeling as well as from the process mining discipline are used to reinforce agent-based decision-making. Whereas agent-technology is used to orchestrate the integration and relationship between the environment and business logic activities, process mining capabilities are mainly used to discover and analyze emergent behavior. Using a functional decomposition approach, we specified three agent types: cyber-physical controller agent, business rule management agent, and emergent behavior detection agent. We use agent-based simulation of a logistics cold chain case study to demonstrate the feasibility of our approach.
|Title of host publication||Proceedings of the 2020 Winter Simulation Conference, WSC|
|Editors||K.-H. Bae, B. Feng, S. Kim, S. Lazarova-Molnar, Z. Zheng, T. Roeder, R. Thiesing|
|Place of Publication||Piscataway, NJ|
|Number of pages||12|
|Publication status||Published - 29 Mar 2021|
|Event||Winter Simulation Conference, WSC 2020: Simulation Drives Innovation - Virtual Conference, Orlando, United States|
Duration: 14 Dec 2020 → 18 Dec 2020
|Conference||Winter Simulation Conference, WSC 2020|
|Abbreviated title||WSC 2020|
|Period||14/12/20 → 18/12/20|
FingerprintDive into the research topics of 'Using agent-based simulation for emergent behavior detection in cyber-physical systems'. Together they form a unique fingerprint.
Data underlying the paper: Using agent-based simulation for emergent behavior detection in cyber-physical systems