Virtualising Space – New Directions for Applications of Agent-Based Modelling in Spatial Economics

Due to enormous technological progress, socio‑economic science has gained new possibilities of investigating complex and not well‑known socio‑economic phenomena. One of the recent promising research approaches is agent‑based modelling (ABM) with connection to geographical (GIS) data. ABM is a bottom‑up research method concerning individuals that live and interact in the artificial environment. In this type of simulation, evolution of the whole system and macro‑level patterns results from individual behaviour of autonomous entities. Combining ABM with GIS data moves the simulation into the real geographical space. Applying this approach provides powerful possibilities of more realistic socio‑economic simulations concerning urban and spatial economics, sociology and psychology. Geosimulation also helps to answer questions about dependencies between geographical space and economic performances of modern cities. In this paper, a closer look at this topic is presented. We deal with the problem of implementation of GIS data into agent‑based modelling software. In the first step of our research procedure, we compare ABM programming platforms, then we chose three of them which provide GIS data support. In the second step, we implement OpenStreetMap GIS data for one of the districts of Poznań into these programming platforms. Finally, we compare the performance of ABM platforms regarding three major criteria: difficulty of programming, GIS data compatibility and available technical support. Our research is the first step in developing a comple Xsocio‑economic urban system under the ABM paradigm.