Process / pipelineSimulation / optimization
贝叶斯基于智能体的建模 — 使用贝叶斯推断校准复杂模拟
贝叶斯基于智能体的建模 (Bayesian Agent-Based Modeling, Bayesian ABM) 将贝叶斯统计推断与基于智能体的模拟相结合，以校准模型参数并量化不确定性。该方法不通过假设固定智能体规则和参数，而是将未知参数视为概率分布，并系统地根据观测数据更新它们，从而得到对模型配置可能性的完整后验分布。
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来源
- Sunnaker, M., Busetto, A. G., Numminen, E., Corander, J., Foll, M., Dessimoz, C. (2013). Approximate Bayesian Computation. PLOS Computational Biology, 9(1), e1002803. DOI: 10.1371/journal.pcbi.1002803 ↗
- Grazzini, J., Richiardi, M. (2015). Estimation of agent-based models by simulated minimum distance. Journal of Economic Dynamics and Control, 51, 148-165. DOI: 10.1016/j.jedc.2014.10.006 ↗
如何引用本页
ScholarGate. (2026, June 3). Bayesian Agent-Based Modeling — Parameter Estimation and Uncertainty Quantification for Agent-Based Models. ScholarGate. https://scholargate.app/zh/simulation/bayesian-agent-based-modeling
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