Multi-actor-based land use modelling: spatial planning using agents

This paper describes a spatial planning model combining a multi-agent simulation (MAS) approach with cellular automata (CA). The model includes individual actor behaviour according to a bottom-up modelling concept. Spatial planning intentions and related decision making of planning actors is defined by agents. CA is used to infer the knowledge needed by the agents to make decisions about the future of a spatial organisation in a certain area. The innovative item of this approach offers a framework for modelling complex land use planning process by extending CA approach with MAS. The modelling approach is demonstrated by the implementation of a pilot model using JAVA and the SWARM agent modelling toolkit. The pilot model itself is applied to a study area near the city of Nijmegen, The Netherlands.

[1]  Guy Engelen,et al.  Cellular Automata as the Basis of Integrated Dynamic Regional Modelling , 1997 .

[2]  Robert M. Itami,et al.  Simulating spatial dynamics: cellular automata theory , 1994 .

[3]  Fulong Wu A linguistic cellular automata simulation approach for sustainable land development in a fast growing region , 1996 .

[4]  Peter Deadman,et al.  Modelling individual behaviour and group performance in an intelligent agent-based simulation of the tragedy of the commons , 1999 .

[5]  G Engelen,et al.  Using cellular automata for integrated modelling of socio-environmental systems , 1995, Environmental monitoring and assessment.

[6]  P. Maes Modeling adaptive autonomous agents , 1993 .

[7]  Nicholas R. Jennings,et al.  On agent-based software engineering , 2000, Artif. Intell..

[8]  F. Kleefmann Planning als zoekinstrument , 1984 .

[9]  Juval Portugali,et al.  Artificial Planning Experience by Means of a Heuristic Cell-Space Model: Simulating International Migration in the Urban Process , 1995 .

[10]  Xia Li,et al.  Modelling sustainable urban development by the integration of constrained cellular automata and GIS , 2000, Int. J. Geogr. Inf. Sci..

[11]  Helen Couclelis,et al.  From Cellular Automata to Urban Models: New Principles for Model Development and Implementation , 1997 .

[12]  D F Wagner,et al.  Cellular Automata and Geographic Information Systems , 1997 .

[13]  Helen Couclelis,et al.  Of Mice and Men: What Rodent Populations Can Teach Us about Complex Spatial Dynamics , 1988 .

[14]  Fulong Wu,et al.  SimLand: A Prototype to Simulate Land Conversion Through the Integrated GIS and CA with AHP-Derived Transition Rules , 1998, Int. J. Geogr. Inf. Sci..

[15]  Michael Batty,et al.  From Cells to Cities , 1994 .

[16]  R. van Lammeren Computergebruik in de ruimtelijke planning : methodologische aspecten van ruimtelijke planvorming met behulp van informatieverwerkende systemen , 1994 .

[17]  Helen Couclelis,et al.  Cellular Worlds: A Framework for Modeling Micro—Macro Dynamics , 1985 .