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

arXiv: https://arxiv.org/abs/2408.08571 · HTML: https://mlsanity.com/paper/2408.08571/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 22 references that are in the map.
- First posted on arXiv 16 Aug 2024.

## Builds on (most cited first, 6 of 6)

- [Predictive Business Process Monitoring with LSTM Neural Networks](https://mlsanity.com/paper/1612.02130/) (2016)
- [Automated Discovery of Business Process Simulation Models from Event Logs](https://mlsanity.com/paper/1910.05404/) (2019)
- [Learning Accurate Business Process Simulation Models from Event Logs via Automated Process Discovery and Deep Learning](https://mlsanity.com/paper/2103.11944/) (2021)
- [Agent Miner: An Algorithm for Discovering Agent Systems from Event Data](https://mlsanity.com/paper/2212.01454/) (2022)
- [Can I Trust My Simulation Model? Measuring the Quality of Business Process Simulation Models](https://mlsanity.com/paper/2303.17463/) (2023)
- [Enhancing Business Process Simulation Models with Extraneous Activity Delays](https://mlsanity.com/paper/2206.14051/) (2022)

## Built on by (most cited first, 8 of 8)

- [Scaling Autonomous Agents via Automatic Reward Modeling And Planning](https://mlsanity.com/paper/2502.12130/) (2025)
- [Agentic Business Process Management: Practitioner Perspectives on Agent Governance in Business Processes](https://mlsanity.com/paper/2504.03693/) (2025)
- [SimBank: from Simulation to Solution in Prescriptive Process Monitoring](https://mlsanity.com/paper/2506.14772/) (2025)
- [Linking Actor Behavior to Process Performance Over Time](https://mlsanity.com/paper/2507.23037/) (2025)
- [Rethinking BPS: A Utility-Based Evaluation Framework](https://mlsanity.com/paper/2505.22316/) (2025)
- [A Divide-and-Conquer Approach for Modeling Arrival Times in Business Process Simulation](https://mlsanity.com/paper/2505.22381/) (2025)
- [Working My Way Back to You: Resource-Centric Next-Activity Prediction](https://mlsanity.com/paper/2508.19016/) (2025)
- [How Will My Business Process Unfold? Predicting Case Suffixes With Start and End Timestamps](https://mlsanity.com/paper/2509.14536/) (2025)

## Abstract (arXiv)

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.