This paper introduces the integration of the Ethnographic Decision Tree Modelling methodology into an evidence-driven lifecycle for developing agent-based social simulations. The manuscript also highlights the development advantages of using an Ethnographic Decision Tree Model to promote accountable validation and detailed justificationof how agent-based models are built. The result from this methodology is a hierarchical, tree-like structure that represents the branching and possible outcomes of the decision-making process, which can then be implemented in an agent-based model. The original methodology grounds the representation of decision-making solely on ethnographic data, yet the discussed adaptation hereby furthers that by allowing the use of survey data. As a result, the final model is a composite based on a richly descriptive dataset containing observations and reported behaviour of individuals engaged in the same activity and context. This in turn is demonstrated to serve as a useful guide for the implementation of behaviour in an social simulations and also serve as a baseline for testing. ©Springer-Verlag Berlin Heidelberg 2014.
CITATION STYLE
Lucas, P. (2014). An adaptation of the Ethnographic Decision Tree Modeling methodology for developing evidence-driven agent-based models. In Advances in Intelligent Systems and Computing (Vol. 229 AISC, pp. 343–350). Springer Verlag. https://doi.org/10.1007/978-3-642-39829-2_30
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