Agent-based modeling – modern concept of GIS modeling

Piotr Dzieszko
Adam Mickiewicz University in Poznan
Faculty of Geographical and Geological Sciences
Institute of Geoecology and Geoinformation
Department of Geoecology
Poland

Katarzyna Bartkowiak
Adam Mickiewicz University in Poznan
Faculty of Geographical and Geological Sciences
Institute of Geoecology and Geoinformation
Department of Geoecology
Poland

Katarzyna Giełda-Pinas
Adam Mickiewicz University in Poznan
Faculty of Geographical and Geological Sciences
Institute of Geoecology and Geoinformation
Department of Geoecology
Poland

Abstract

One of the most prospective bottom-up approaches to modeling of human-environment relations is agent-based modeling (ABM). ABM is a modern technique more and more often used in Geographical Information Science. It is based on entities called agents which can make spatial decisions. They can also exchange information with each other. Moreover, they have attributes which allow to describe their actual state. In classical approach to modeling, all entities are often quite similar. It is possible to create a model with very similar entities within ABM. These entities may behave slightly differently. Agents can have identical attributes and quite different decision rules. It allows a user to apply randomness in a model which is really crucial in environmental studies. ABM and simulation can be traced to investigations into complex adaptive systems, the evolution of cooperation and artificial life. Unlike other modeling approaches, ABM begins and ends with the agent’s perspective. The application of ABM to simulating dynamics within GIS has seen a considerable increase over the last decade. Both agents and decisions they make have spatial reference. So linking AMB with GIS is a natural consequence of these two techniques development. ABM is normally a very useful decision making process, in extreme events simulation, forecasting the environment development, spatial planning, and environmental impact assessment.
In this paper. possibilities of the use of ABM were presented. ABM is a modern research technique within GIS. Most important features of ABM were described as well as well-known software platforms and toolsets for agent-based model creating. Finally, information when the ABM can be especially useful in research work and how to select the best system which will fit the standards of our model was provided.

Keywords:

agent-based modelling; geographical information systems; geomodeling

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References

Abdou M., Hamill L., Gilbert N., 2012: Designing and building an Agent-Based Model. [W:] Heppenstall A. J., Crooks A. T., See L. M., Batty M. (red.), Agent-Based Models of Geographical Systems, Springer, Dordrecht: 141-165.

Axelrod R., 1997: The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press, Princeton.

Batty M., Torrens P. M., 2005: Modelling and Prediction in a Complex World. Futures, 37 (7): 745-766.

Bernard R. N., 1999: Using Adaptive Agent-Based Simulation Models to Assist Planners. [W:] Policy Development: The Case of Rent Control. Working Paper 99-07-052, Santa Fe, New Mexico, Santa Fe Institute.

Bonabeau E., 2002: Agent-based modelling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 99 (3): 7280-7287.

Brown D. G., 2006: Agent-Based Models. [W:] Geist H. (red.), The Earth’s Changing Land: An Encyclopedia of Land-Use and Land-Cover Change. Greenwood Publishing Group, Westport: 7-13.

Brown D. G., Page S. E., Riolo R., Zellner M., Rand W., 2005: Path dependence and the validation of agent-based spatial models of land use. International Journal of Geographical Information Science 19 (2): 153-174.

Couclelis H., 2002: Modelling Frameworks, Paradigms, and Approaches. [W:] Clarke K. C., Parks B. E., Crane M. P. (red.), Geographic Information Systems and Environmental Modeling. London: Prentice Hall: 36-50.

Crooks A. T., Castle C., 2012: The Integration of Agent-Based Modeling and Geographical Information for Geospatial Simulation. [W:] Heppenstall A. J., Crooks A. T., See L. M., Batty M. (red.), Agent-Based Models of Geographical Systems. Springer, Dordrecht: 219-252.

Crooks A. T., Heppenstall A. J., 2012: Introduction to Agent-Based Modelling. [W:] Heppenstall A. J., Crooks A. T., See L. M., Batty M. (red.), Agent-Based Models of Geographical Systems. Springer, Dordrecht: 141-165.

Gilbert N. 2007: Agent-based models. London: Sage.

Gilbert N., Terna P., 2000: How to Build and Use Agent-Based Models in Social Science, Mind and Society, 1 (1): 57-72.

Gwynne S., Galea E. R., Lawrence P. J., Filippidis L., 2001: Modelling Occupant Interaction with Fire Conditions Using the Building EXODUS Evacuation Model. Fire Safety Journal, 36 (4): 327-357.

Johnston K.M., North M.J., Brown D.G., 2012: Introducing Agent-Based Modeling in the GIS Environment. [W:] Johnston K. M. (red.), Agent Analyst - Agent-Based Modeling in ArcGIS, Redlands, Esri Press: 1-30.

Ligmann-Zielinska A., 2010: Agent-based models. [W:] Encyclopedia of Geography. SAGE Publications, http://www.sage-ereference.com/geography/Article_n14.html

Longley P. A., Goodchild M. F., Maguire D. J., Rhind, D. W., 2005: Geographical Information Systems and Science. Wiley, New York, 2 wyd.

Macal C. M., North M. J., 2005: Tutorial on agent-based modelling and simulation. [W:] Euhl M. E., Steiger N. M., Armstrong F. B., Joines J. A. (red.), Proceedings of the 2005 Winter Simulation Conference, Orlando: 2-15.

Macy M., Willer R., 2002: From factors to actors: Computational sociology and agent-based modeling, Annual Review of Sociology, 28: 143-166.

Nagel K., Rasmussen S., 1994: Traffic at the Edge of Chaos. [W:] Brooks R. (red.), Artificial life, MIT Press, Cambridge: 222–236.

Nagel, K., 2003: Traffic networks. [W:] Bornholdt S, Schuster H. (eds.), Handbook of graphs and networks: From the genome to the internet: 248-272, New York: Wiley.

North M. J., Macal C. M., 2007: Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation. Oxford University Press, New York.

O’Sullivan D., Millington J., Perry G., Wainwright J., 2012: Agent-Based Models – Because They’re Worth It? [W:] Heppenstall A. J., Crooks A. T.,. See L. M, Batty M. (red.), Agent-Based Models of Geographical Systems, Springer, Dordrecht: 69-84.

Parry H. R., Bithnell M., 2012: Large scale agent-based modelling: A review and guidelines for model scaling. [W:] Heppenstall A. J., Crooks A. T., See L. M., Batty M. (red.), Agent-Based Models of Geographical Systems, Springer, Dordrecht: 525-542.

Zwoliński Z., 2009: Rozwój myśli geoinformacyjnej. [W:] Zwoliński Z. (red.), GIS – platforma geografii, Bogucki Wyd. Naukowe, Poznań: 9-21.