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Juliette Rouchier, Claudio Cioffi-Revilla, J. Gary Polhill and Keiki Takadama (2008)

Progress in Model-To-Model Analysis

Journal of Artificial Societies and Social Simulation vol. 11, no. 2 8
<http://jasss.soc.surrey.ac.uk/11/2/8.html>

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Received: 03-Aug-2007    Accepted: 03-Aug-2007    Published: 31-Mar-2008

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* Abstract

Keywords:
Social Simulation, Agent-Based Modelling, Comparative Computational Methodology, Validation, Replication

*

1.1
The model-to-model series of workshops was set up with a view to gathering work on comparative analysis of social simulations. The first workshop was held in Marseille, March 2003, to counter a perceived dearth of comparison and transfer of knowledge among a burgeoning number of models in the area (Hales, Rouchier and Edmonds 2003). Since then, a second workshop was held alongside ESSA 2004 in Valladolid, the forum of JASSS has been dedicated to model comparison work, and now, after a relatively long interval, a third workshop was held in Marseille, March 2007.

1.2
Comparative analysis of social simulations can draw on the rich and distinguished tradition of comparative social research (Bartolini 1993; Dion 2003; Przeworksi and Teune 1970; Saberwal 1987; Sartori 1991). Despite a growing interest in model-to-model analysis, there is arguably still not enough of it being done. It is not difficult to suggest reasons for this. Developing one's own model is much more fun than studying or developing syntheses of others' work. Model-to-model work also generally tends to be very time-consuming. Comparative modelling research can be broadly categorised into a number of areas, each of which has its own challenges:

1.3
The third Model-to-Model workshop covered some of the latest developments in these areas. Fifteen papers were presented from twenty-seven peer-reviewed submissions, and there was one invited presentation. Of the sixteen papers in the workshop, eight reflecting the breadth of discussions have been selected for inclusion in this special issue. We introduce them below in no particular order. The full proceedings of the workshop are available at http://m2m2007.macaulay.ac.uk/.

1.4
Izquierdo, Izquierdo, and Gotts replicate Macy and Flache's (2002) work with 2×2 social dilemma games, using mathematical analysis to understand the sensitivities of the model to different learning rates and the introduction of stochasticity.

1.5
Vilà develops an analytical model of Bertrand competition alongside a simulation, comparing the effects of using the simulation to relax the restrictive assumptions of the mathematical analysis on the results obtained. In a challenge to what is sometimes claimed by practitioners in social simulation, Vilà finds that relaxing the assumptions in the simulation model does not change the conclusions from the mathematical analysis.

1.6
Huet and Deffuant study the primacy effect (the effect of the order in which information is presented on perceptions), at the individual and population levels. They also complement their simulation work with mathematical analysis and conclude that the latter assisted them with understanding their model.

1.7
Polhill, Parker, Brown, and Grimm discuss the application of a proposed document structure for describing individual based models in ecology (Grimm et al. 2006) to three agent-based models of land use change. They find Grimm's protocol, which was intended to be applicable to social as well as ecological models, is indeed useful for structuring social simulation model descriptions in journal articles. However, some refinements are needed to capture all the agent-based simulation work in the social sciences.

1.8
Merlone, Sonnessa, and Terna, taking Edmonds and Hales' (2003) recommendations to heart, use three separate implementations in radically different simulation architectures to study population changes in industrial districts. They find differences in the floating point and pseudo-random number environments of each architecture prevent exact replication of their results, but are able to generate qualitatively similar results, that, through the multiple implementation strategy, are arguably more trustworthy.

1.9
Takadama, Kawai, and Koyama apply validation at both the micro and macro level to model agents who can reproduce not only human-like behaviours externally but also human-like thinking internally. Such agent modelling is investigated on reinforcement learning in an agent-based simulation of a sequential bargaining game. Their validation is based on experiments with human subjects, and they find that a certain configuration of the reinforcement learning algorithm is able, within the context of the game, to reproduce both the observed human behaviour and thinking.

1.10
Janssen, Alessa, Barton, Bergin, and Lee report on the establishment of the Open Agent-Based Modelling Consortium, a community forum in which to develop best practice, protocols, and standards. This is a significant initiative, that should be supported along with others like it.

1.11
As in earlier workshops, the timetable was scheduled to allow plenty of time for presentation and discussion of each paper. We, and all who attended, believe the event was a success, and express the hope that in the future, model-to-model workshops will be held more regularly than in the past.

* Acknowledgements

The programme committee thanks the Centre National de la Recherche Scientifique (CNRS), Groupement de Recherche en Econome Quantitative d'Aix Marseille (GREQAM) and the European Social Simulation Association (ESSA) for their financial and organisational support for the workshop.

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