A framework for the calibration of social simulation models
Abstract
Simulation with agent-based models is increasingly used in the study of complex socio-technical systems and in social simulation in general. This paradigm offers a number of attractive features, namely the possibility of modeling emergent phenomena within large populations. As a consequence, often the quantity in need of calibration may be a distribution over the population whose relation with the parameters of the model is analytically intractable. Nevertheless, we can simulate. In this paper we present a simulation-based framework for the calibration of agent-based models with distributional output based on indirect inference. We illustrate our method step by step on a model of norm emergence in an online community of peer production, using data from three large Wikipedia communities. Model fit and diagnostics are discussed.
Cite
@article{arxiv.1305.3842,
title = {A framework for the calibration of social simulation models},
author = {Giovanni Luca Ciampaglia},
journal= {arXiv preprint arXiv:1305.3842},
year = {2015}
}
Comments
31 pages, 7 figures, accepted on Adv. Compl. Sys