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A Conceptual Framework for Digital Twins of Multi-agent Systems

Procedia Computer Science 2025年 257卷 321-328页

作者： Hui Min Lee Ruhollah Jamali Sanja Lazarova-Molnar Institute of Applied Informatics and Formal Description Methods Karlsruhe Institute of Technology Kaiserstr. 89 Karlsruhe 76133 Germany The Maersk Mc Kinney Moller Institute University of Southern Denmark Campusvej 55 Odense 5230 Denmark

Multi-agent Systems (MASs) are complex systems made up of agents that can be any entities with the ability to interact autonomously and make decentralized decision-making to solve complex problems. data-driven agent-based modeling and Simulation (DDABMS) equips MASs with access to decisions based on near-real-time data, allowing for more informed decisions for systems’ enhancements. Digital Twins (DTs) can further enhance MASs by serving as virtual replicas that enable what-if scenarios exploration and allow continuous validation and refinement of the underlying models with real-time data from MASs. However, we discovered a gap in systematically integrating DTs with DDABMS, as existing efforts focus on specific problems and domains rather than providing a generalized framework to develop DTs with DDABMS. This paper addresses this gap by proposing a generalized framework to develop DTs for MASs with DDABMS. To demonstrate the practicability of our proposed framework for modeling and simulation of complex systems, we present an illustrative case study based on an epidemiological Susceptible-Infected-Recovered model.

关键词： digital twins multi-agent systems data-driven agent-based modeling agent-based modeling simulation decision making

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A Conceptual Framework for Digital Twins of Multi-agent Systems 16

A Conceptual Framework for Digital Twins of Multi-Agent Syst...

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16th International Conference on Ambient Systems, Networks and Technologies Networks, ANT 2025 / 8th International Conference on Emerging data and Industry 4.0, EDI40 2025

作者： Lee, Hui Min Jamali, Ruhollah Lazarova-Molnar, Sanja Institute of Applied Informatics and Formal Description Methods Karlsruhe Institute of Technology Kaiserstr. 89 Karlsruhe 76133 Germany The Maersk Mc Kinney Moller Institute University of Southern Denmark Campusvej 55 Odense 5230 Denmark

Multi-agent Systems (MASs) are complex systems made up of agents that can be any entities with the ability to interact autonomously and make decentralized decision-making to solve complex problems. data-driven agent-based modeling and Simulation (DDABMS) equips MASs with access to decisions based on near-real-time data, allowing for more informed decisions for systems' enhancements. Digital Twins (DTs) can further enhance MASs by serving as virtual replicas that enable what-if scenarios exploration and allow continuous validation and refinement of the underlying models with real-time data from MASs. However, we discovered a gap in systematically integrating DTs with DDABMS, as existing efforts focus on specific problems and domains rather than providing a generalized framework to develop DTs with DDABMS. This paper addresses this gap by proposing a generalized framework to develop DTs for MASs with DDABMS. To demonstrate the practicability of our proposed framework for modeling and simulation of complex systems, we present an illustrative case study based on an epidemiological Susceptible-Infected-Recovered model. © 2025 Elsevier B.V.. All rights reserved.

关键词： agent-based modeling data-driven agent-based modeling decision making digital twins multi-agent systems simulation

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