Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
Gemini 2.5 Pro
GPT-5
GPT-4o
DeepSeek R1 via Azure
2000 character limit reached

Examining inverse generative social science to study targets of interest (2407.13474v1)

Published 18 Jul 2024 in stat.CO

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 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.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.