arXiv 2408.085712024-08-16cs.MAcs.AI

AgentSimulator：一种基于智能体的数据驱动业务流程仿真方法

AgentSimulator: An Agent-based Approach for Data-driven Business Process Simulation

SAP Signavio（思爱普 Signavio）；University of Mannheim（曼海姆大学）；University of Vienna（维也纳大学）

Lukas Kirchdorfer, Robert Blümel, Timotheus Kampik, Han van der Aa, Heiner Stuckenschmidt

AI总结：

针对传统控制流优先的业务流程仿真方法无法准确捕捉现实流程中差异化资源行为与去中心化决策动态的问题，本文提出资源优先的AgentSimulator方法，从事件日志挖掘多智能体系统建模资源行为与交互模式，实验证明其精度达SOTA、计算耗时更低且可解释性、场景适配性强。

摘要：

业务流程仿真（BPS）是一种用于评估不同场景下流程性能的通用技术。传统BPS方法采用控制流优先的视角，通过为流程模型添加仿真参数来实现。尽管这类方法能够模拟集中编排的流程（如工作流系统支持的流程）的行为，但当前的控制流优先方法无法准确捕捉现实流程中涉及的差异化资源行为和去中心化决策的动态特性。针对这一问题，本文提出了AgentSimulator，这是一种资源优先的BPS方法，它从事件日志中挖掘多智能体系统，对差异化的资源行为和交互模式进行建模，以仿真底层流程。我们的实验表明，AgentSimulator达到了当前最优的仿真精度，计算时间显著低于现有方法，同时具备高可解释性，能够适配不同类型的流程执行场景。

英文摘要：

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.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

AI总结：

摘要：

英文摘要：

相关论文