Which Sensitivity Analysis Method Should I Use for My Agent-Based Model?
Authored by Arend Ligtenberg, Broeke Guus ten, Voorn George van
Date Published: 2016
DOI: 10.18564/jasss.2857
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Abstract
Existing methodologies of sensitivity analysis may be insufficient for a
proper analysis of Agent-based Models (ABMs). Most ABMs consist of
multiple levels, contain various nonlinear interactions, and display
emergent behaviour. This limits the information content that follows
from the classical sensitivity analysis methodologies that link model
output to model input. In this paper we evaluate the performance of
three well-known methodologies for sensitivity analysis. The three
methodologies are extended OFAT (one-factor-at-a-time), and proportional
assigning of output variance by means of model fitting and by means of
Sobol' decomposition. The methodologies are applied to a case study of
limited complexity consisting of free-roaming and procreating agents
that make harvest decisions with regard to a diffusing renewable
resource. We find that each methodology has its own merits and exposes
useful information, yet none of them provide a complete picture of model
behaviour. We recommend extended OAT as the starting point for
sensitivity analysis of an ABM, for its use in uncovering the mechanisms
and patterns that the ABM produces.
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