Mario Paolucci

Two Scenarios for Crowdsourcing Simulation

In this paper, we trace a line through the recent story of agent-based social simulation from the point of view of the LABBS, the laboratory of agent-based social simulation that Cristiano Castelfranchi has contributed to create and helped grow. From this observatory, we deploy a set of arguments defending the need for social simulation as one of the best chances we have to make a much needed step forward in the scientific endeavor of the twenty first century: understanding society. Building on these arguments, we point out several reasons that caused social simulation to fall several measures short of the big challenge, discussing some famous examples from the literature. We then introduce the concept of crowdsourcing, trying to elaborate on how it could reshape this methodology for computational social science.