Document details for 'Comparing agent-based model versions using Approximate Bayesian Computation'

Authors Polhill, J.G., Gair, JG, Brewer, M.J., Gotts, N. and Butler, A.
Publication details In "Social Simulation Conference 2018". SSC 2018, Stockholm, Sweden.
Publisher details SSC 2018, Stockholm, Sweden
Keywords Approximate Bayesian Computation, ontologies, model comparison
Abstract

Structural uncertainty in modelling social systems is a perennial problem, since there may be several ways to create formal descriptions and characterizations of the system itself and the dynamics operating therein. In this paper, we apply Approximate Bayesian Computation to the comparison of several versions of a model of domestic energy demand in north east Scotland. We demonstrate that these versions, which switch 'on' and 'off' various features in the software used to implement the model, show considerable differences in relative performance. In the case of the model itself, we are able to show which versions are more credible with respect to the data. More generally, however, the methodology described here shows how issues with structural uncertainty can be addressed in empirical agent-based modelling.

Last updated 2018-12-03
Links
  1. Conference webpage
    http://ssc2018.dsv.su.se/

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