Private Agent-Based Modeling
<|reference_start|>Private Agent-Based Modeling: The practical utility of agent-based models in decision-making relies on their capacity to accurately replicate populations while seamlessly integrating real-world data streams. Yet, the incorporation of such data poses significant challenges due to privacy concerns. To address this issue, we introduce a paradigm for private agent-based modeling wherein the simulation, calibration, and analysis of agent-based models can be achieved without centralizing the agents attributes or interactions. The key insight is to leverage techniques from secure multi-party computation to design protocols for decentralized computation in agent-based models. This ensures the confidentiality of the simulated agents without compromising on simulation accuracy. We showcase our protocols on a case study with an epidemiological simulation comprising over 150,000 agents. We believe this is a critical step towards deploying agent-based models to real-world applications.<|reference_end|>
@article{chopra2024private,
    title={Private Agent-Based Modeling},
    author={Ayush Chopra, Arnau Quera-Bofarull, Nurullah Giray-Kuru, Michael
  Wooldridge, Ramesh Raskar},
    journal={arXiv preprint arXiv:2404.12983},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.12983},
    primaryClass={cs.MA cs.CR cs.SI}
}