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Alternative Approaches to the Empirical Validation of Agent-Based Models

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Author Info
Scott Moss ()
Abstract

This paper draws on the metaphor of a spectrum of models ranging from the most theory-driven to the most evidence-driven. The issue of concern is the practice and criteria that will be appro- priate to validation of different models. In order to address this concern, two modelling approaches are investigated in some detailed – one from each end of our metaphorical spectrum. Windrum et al. (2007) (http://jasss.soc.surrey.ac.uk/10/2/8.html) claimed strong similarities between agent based social simulation and conventional social science – specifically econometric – approaches to empirical modelling and on that basis considered how econometric validation techniques might be used in empirical social simulations more broadly. An alternative is the approach of the French school of \'companion modelling\' associated with Bousquet, Barreteau, Le Page and others which engages stakeholders in the modelling and validation process. The conventional approach is con- strained by prior theory and the French school approach by evidence. In this sense they are at opposite ends of the theory-evidence spectrum. The problems for validation identified by Windrum et al. are shown to be irrelevant to companion modelling which readily incorporate complexity due to realistically descriptive specifications of individual behaviour and social interaction. The result combines the precision of formal approaches with the richness of narrative scenarios. Companion modelling is therefore found to be practicable and to achieve what is claimed for it and this alone is a key difference from conventional social science including agent based computational economics.

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Article provided by Journal of Artificial Societies and Social Simulation in its journal Journal of Artificial Societies and Social Simulation.

Volume (Year): 11 (2007)
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Handle: RePEc:jas:jasssj:2007-61-2

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Related research
Keywords: Social Simulation; Validation; Companion Modelling; Data Generating Mechanisms; Complexity;

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This page was last updated on 2009-11-29.


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