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Researchers have become increasingly interested in the potential use of agent-based modelling for the prediction of social phenomena, motivated by the desire, first, to further cement the method’s scientific status and, second, to participate in other scenarios, particularly in the aid of decision-making. This article contributes to the current discussion on prediction from the perspective of the disciplinary organisation of agent-based social simulation. It addresses conceptual and practical challenges pertaining to the community of practitioners, rather than individual instances of modelling. As such, it provides recommendations that invite both collective critical discussion and cooperation. The first two sections review conceptual challenges associated with the concept of prediction and its instantiation in the computational modelling of complex social phenomena. They identify methodological gaps and disagreements that warrant further analysis. The second two sections consider practical challenges related to the lack of a prediction framework that, on one hand, gives meaning and accommodates everyday prediction practices and, on the other hand, establishes more clearly the connection between prediction and other epistemic goals. This coordination at the practical level, it is claimed, might help to better position prediction with agent-based modelling within the larger social science’s methodological landscape.

What kind of prediction? Evaluating different facets of prediction in agent-based social simulation