AgentSimulator: An Agent-based Approach for Data-driven Business Process Simulation
<|reference_start|>AgentSimulator: An Agent-based Approach for Data-driven Business Process Simulation: Business process simulation (BPS) is a versatile technique for estimating process performance across various scenarios. Traditionally, BPS approaches employ a control-flow-first perspective by enriching a process model with simulation parameters. Although such approaches can mimic the behavior of centrally orchestrated processes, such as those supported by workflow systems, current control-flow-first approaches cannot faithfully capture the dynamics of real-world processes that involve distinct resource behavior and decentralized decision-making. Recognizing this issue, this paper introduces AgentSimulator, a resource-first BPS approach that discovers a multi-agent system from an event log, modeling distinct resource behaviors and interaction patterns to simulate the underlying process. Our experiments show that AgentSimulator achieves state-of-the-art simulation accuracy with significantly lower computation times than existing approaches while providing high interpretability and adaptability to different types of process-execution scenarios.<|reference_end|>
@article{kirchdorfer2024agentsimulator:,
    title={AgentSimulator: An Agent-based Approach for Data-driven Business Process
  Simulation},
    author={Lukas Kirchdorfer, Robert Bl"umel, Timotheus Kampik, Han van der Aa,
  Heiner Stuckenschmidt},
    journal={arXiv preprint arXiv:2408.08571},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.08571},
    primaryClass={cs.MA cs.AI}
}