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

• Authors: Marcin Wozniak

Title variants

Wirtualizacja przestrzeni – nowe kierunki aplikacji modelowania wieloagentowego w ekonomii przestrzennej

• Languages of publication: EN

Abstracts

EN

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.

PL

W związku z ogromnym postępem technologicznym przed naukami społeczno‑ekonomicznymi otworzyły się nowe płaszczyzny badań złożonych i nie do końca poznanych zjawisk. Jednym z podejść badawczych w tych obszarach jest tzw. modelowanie wieloagentowe (Agent‑Based Modeling) w połączeniu z danymi geograficznymi (GIS). Modelowanie wieloagentowe to metoda, w której budowane są złożone systemy składające się z autonomicznych jednostek (agentów). Między agentami zachodzą interakcje na poziomie mikro, których rezultatem jest ewolucja całego systemu na poziomie makro. Jednym z interesujących trendów modelowania wieloagentowego jest geosymulacja, czyli symulacja wieloagentowa osadzona w świecie wirtualnym, będącym odpowiednikiem realnej, fizycznej przestrzeni. Geosymulacja umożliwia zaawansowane i bardziej realistyczne badania na gruncie ekonomii przestrzennej, socjologii czy psychologii. Niniejszy artykuł pogłębia tę problematykę. Dokonano w nim identyfikacji i porównania dostępnych platform do symulacji wieloagentowej i wybrano trzy, które posiadają wsparcie dla danych geograficznych (GIS). Na tych platformach zaimplementowano dane GIS o zagospodarowaniu przestrzennym dla jednej z dzielnic Poznania. Dokonano również porównania funkcjonalności oprogramowania pod kątem trzech kryteriów: trudności programowania, funkcjonalności i współpracy z danymi GIS oraz dostępności materiałów szkoleniowych. Badania te stanowią wstępny etap opracowania złożonego, społeczno‑ekonomicznego systemu miejskiego, osadzonego w paradygmacie modelowania wieloagentowego.

Keywords

EN

agent‑based modelling; geographical information systems; urban economics; spatial economics

PL

modelowanie wieloagentowe; systemy informacji geograficznej; ekonomia miast; ekonomia przestrzenna; modelowanie wieloagentowe; systemy informacji geograficznej; ekonomia miast; ekonomia przestrzenna

• Publisher: Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
• Journal: Acta Universitatis Lodziensis. Folia Oeconomica
• Year: 2020
• Volume: 1
• Issue: 346
• Pages: 7-26

Dates

published

2020-02-03

Contributors

author

Marcin Wozniak

• Adam Mickiewicz University in Poznań, Faculty of Socio-Economic Geography and Spatial Management

• https://orcid.org/0000-0002-3213-229X

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Identifiers

DOI

10.18778/0208-6018.346.01