Abstract
In order to ensure simulations reproducibility, particular attention must be payed to the specification of its model. This requires adequate design methodologies, that enlightens modelers on possible implementation ambiguities – and biases – their model might have. Yet, because of not adapted knowledge representation, current reactive simulation design methodologies lack specifications concerning interaction selection, especially in stochastic behaviors. Thanks to the interaction-oriented methodology IODA – which knowledge representation is fit to handle such problems – this paper provides simple guidelines to describe interaction selection. These guidelines use a subsumption like-structure, and focus the design of interaction selection on two points : how the selection takes place – for instance first select the interaction, and then select the partner of the interaction, or first a partner and then an interaction – and the nature of each selection – for instance at random, or with a utility function. This provides a valuable communication support between modelers and computer scientists, that makes the interpretation of the model and its implementation clearer, and the identification of ambiguities and biases easier.
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Kubera, Y., Mathieu, P., Picault, S. (2009). How to Avoid Biases in Reactive Simulations. In: Demazeau, Y., Pavón, J., Corchado, J.M., Bajo, J. (eds) 7th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2009). Advances in Intelligent and Soft Computing, vol 55. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00487-2_11
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DOI: https://doi.org/10.1007/978-3-642-00487-2_11
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