Using agent-based simulation for emergent behavior detection in cyber-physical systems

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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.
Original languageEnglish
Title of host publicationProceedings of the 2020 Winter Simulation Conference
Number of pages12
Publication statusAccepted/In press - 2020
EventWinter Simulation Conference, WSC 2020: Simulation Drives Innovation - Virtual Conference, Orlando, United States
Duration: 14 Dec 202018 Dec 2020


ConferenceWinter Simulation Conference, WSC 2020
Abbreviated titleWSC 2020
CountryUnited States
Internet address

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