An Adaptation of the Ethnographic Decision Tree Modeling Methodology for Developing Evidence-Driven Agent-Based Models

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 229)

Abstract

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 justification of 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.

Keywords

methodology evidence qualitative development validation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Geary InstituteUniversity College DublinDublinIreland
  2. 2.Maastricht School of ManagementMaastrichtThe Netherlands

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