How to Avoid Biases in Reactive Simulations

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.