Agent-based models tend to be more and more complex. In order to cope with this increase of complexity, powerful modeling and simulation tools are required. These last years have seen the development of several platforms dedicated to the development of agent-based models. While some of them are still limited to the development of simple models, others allow to develop rich and complex models. Among them, the GAMA modeling and simulation platform is aimed at supporting the design of spatialized, multiple-paradigms and multiple-scales models. Several papers have already introduced GAMA, notably in earlier PRIMA conferences, and we would like, in this paper, to introduce the new features provided by GAMA 1.6, the latest revision to date of the platform. In particular, we present its capabilities concerning the tight combination of 3D visualization, GIS data management, and multi-level modeling. In addition, we present some examples of real projects that rely on GAMA to develop complex models.
The agent-based modeling is now widely used to study complex systems. Its ability to represent several levels of interaction along a detailed (complex) environment representation favored such a development. However, in many models, these capabilities are not fully used. Indeed, only simple, usually discrete, environment representation and one level of interaction (rarely two or three) are considered in most of the agent-based models. The major reason behind this fact is the lack of simulation platforms assisting the work of modelers in these domains. To tackle this problem, we developed a new simulation platform, GAMA. This platform allows modelers to define spatially explicit and multi-levels models. In particular, it integrates powerful tools coming from Geographic Information Systems (GIS) and Data Mining easing the modeling and analysis efforts. In this paper, we present how this platform addresses these issues and how such tools are available right out of the box to modelers.
1 January 2022 in Journal of Artificial Societies and Social Simulation