Examining inverse generative social science to study targets of interest

Thomas Chesney, Asif Jaffer, Robert Pasley
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Abstract

We assess an emerging simulation research method -- Inverse Generative Social Science (IGSS) \citep{Epstein23a} -- that harnesses the power of evolution by natural selection to model and explain complex targets. Drawing on a review of recent papers that use IGSS, and by applying it in two different studies of conflict, we here assess its potential both as a modelling approach and as formal theory. We find that IGSS has potential for research in studies of organistions. IGSS offers two huge advantages over most other approaches to modelling. 1) IGSS has the potential to fit complex non-linear models to a target and 2) the models have the potential to be interpreted as social theory. The paper presents IGSS to a new audience, illustrates how it can contribute, and provides software that can be used as a basis of an IGSS study.
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考察逆生成社会科学,研究感兴趣的目标
我们评估了一种新兴的模拟研究方法--逆生成社会科学(Inverse Generative SocialScience,IGSS)--它利用自然选择进化的力量来模拟和解释复杂的目标。通过对近期使用 IGSS 的论文进行回顾,并将其应用于两项不同的冲突研究,我们在此评估了 IGSS 作为建模方法和形式理论的潜力。我们发现,IGSS 在组织研究方面具有潜力。与大多数其他建模方法相比,IGSS 具有两个巨大优势。1)IGSS 具有将复杂的非线性模型与目标相匹配的潜力;2)模型具有被解释为社会理论的潜力。本文向新读者介绍了 IGSS,说明了 IGSS 的贡献,并提供了可用作 IGSS 研究基础的软件。
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