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Model-To-Model Analysis

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Abstract

In recent years there has been an explosion of published literature utilising Multi-Agent-Based Simulation (MABS) to study social, biological and artificial systems. This kind of work is evidenced within JASSS but is increasingly becoming part of mainstream practice across many disciplines. However, despite this plethora of interesting models, they are rarely compared, built-on or transferred between researchers. It would seem there is a dearth of "model-to-model" analysis. Rather researchers tend to work in isolation, designing all their models from scratch and reporting their results without anyone else reproducing what they found. Although the opposite extreme, where all that seems to happen is the next twist on an existing model, is not to be wished for, there are considerable dangers if everybody only works on their own model. Part of the reason for this is that models tend to be very seductive – especially to the person who has built the model. What is needed is a third person to check the results. However it is not always clear how people who are not the modeller can interpret or utilise such results, because it is very difficult to replicate simulation models from what is reported in papers. It was for these reasons that we called on the MABS community to submit papers for a model-to-model (M2M) workshop. The aim of the workshop was to gather researchers in MABS who were interested in understanding and furthering the transferability of knowledge between models. We received fourteen submissions from which (after a process of peer review) eight were presented at the workshop. Of the six articles that comprise this special issue, five were presented at the workshop.

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File URL: http://jasss.soc.surrey.ac.uk/6/4/5.html
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Bibliographic Info

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

Volume (Year): 6 (2003)
Issue (Month): 4 ()
Pages: 5

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Handle: RePEc:jas:jasssj:2003-26-1

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Keywords: Comparison of models; simulation methodology; transferability of knowledge;

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Cited by:
  1. Martin Neumann, 2007. "Complexity of social stability: a model-to-model analysis of Yugoslavia's decline," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 5(2), pages 92-111.
  2. İlker Yıldırım & Pınar Yolum, 2009. "Hybrid models for achieving and maintaining cooperative symbiotic groups," Mind and Society: Cognitive Studies in Economics and Social Sciences, Fondazione Rosselli, vol. 8(2), pages 243-258, December.
  3. Wersching, Klaus, 2010. "Schumpeterian competition, technological regimes and learning through knowledge spillover," Journal of Economic Behavior & Organization, Elsevier, vol. 75(3), pages 482-493, September.
  4. Claudio Cioffi-Revilla, 2010. "A Methodology for Complex Social Simulations," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 7.
  5. Pierre Livet & Jean-Pierre Muller & Denis Phan & Lena Sanders, 2010. "Ontology, a Mediator for Agent-Based Modeling in Social Science," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 3.
  6. J. Gary Polhill, 2010. "ODD Updated," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(4), pages 9.
  7. Denis Phan & Franck Varenne, 2010. "Agent-Based Models and Simulations in Economics and Social Sciences: From Conceptual Exploration to Distinct Ways of Experimenting," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 5.
  8. Wolfgang Radax & Bernhard Rengs, 2010. "Prospects and Pitfalls of Statistical Testing: Insights from Replicating the Demographic Prisoner's Dilemma," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(4), pages 1.

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