Laboratory of Agent Based Social Simulation

MABS’12 – The Thirteenth International Workshop on Multi-Agent-Based Simulation
Multi-Agent Simulation of/and the Society
@AAMAS 2012
Valencia, Spain
4th-8th June 2012

http://www.irit.fr/mabs2012

Aims and scope. The meeting of researchers from MAS engineering and the social/economic/organizational sciences is extensively recognized for its role in cross-fertilization, and has undoubtedly been an important source of inspiration for the body of knowledge that has been produced in the MAS area. Multi-Agent Based Simulation (MABS) is a vibrant inter-disciplinary area which brings together researchers within the agent-based social simulation community (ABSS) and the Multiagent Systems community (MAS).
The focus of ABSS is on simulating and organization social behaviours in order to understand real social systems via the development and testing of new concepts. The focus of MAS is on the solution of hard engineering problems related to the construction, deployment and efficient operation of multiagent systems.

Distributed Punishment as a Norm-Signalling Tool@AAMAS2012

As the FuturICT coordination action rushes ahead, we point out some of the dissemination materials that this lab helped to build:

Videos with the FututICT message: a documentary on FuturICT and Rosaria’s interview

Leaflets on the Living Earth Simulator and on the Crime Exploratory.

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.