Examining inverse generative social science to study targets of interest
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866914876417376256 |
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| author | Chesney, Thomas Jaffer, Asif Pasley, Robert |
| author_facet | Chesney, Thomas Jaffer, Asif Pasley, Robert |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_13474 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Examining inverse generative social science to study targets of interest Chesney, Thomas Jaffer, Asif Pasley, Robert Computation 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. |
| title | Examining inverse generative social science to study targets of interest |
| topic | Computation |
| url | https://arxiv.org/abs/2407.13474 |