Agent-based modeling (ABM) has transformed social science research by allowing researchers to replicate or generate the emergence of empirically complex social phenomena from a set of relatively simple agent-based rules at the micro-level. Swarm, RePast, Ascape, and others currently provide simulation environments for ABM social science research. After Swarm�—�arguably the first widely used ABM simulator employed in the social sciences�—�subsequent simulators have sought to enhance available simulation tools and computational capabilities by providing additional functionalities and formal modeling facilities. Here we present MASON (Multi-Agent Simulator Of Neighborhoods), following in a similar tradition that seeks to enhance the power and diversity of the available scientific toolkit in computational social science. MASON is intended to provide a core of facilities useful not only to social science but to other agent-based modeling fields such as artificial intelligence and robotics. We believe this can foster useful “cross-pollination ” between such diverse disciplines, and further that MASON's additional facilities will become increasing important as social complexity simulation matures and grows into new approaches. We illustrate the new MASON simulation library with a replication of HeatBugs and a demonstration of MASON applied to two challenging case studies: ant-like foragers and micro-aerial agents. Other applications are also being developed. The HeatBugs replication and the two new applications provide an idea of MASON’s potential for computational social science and artificial societies
To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.