The integration of agent-based modelling and geographical information for geospatial simulation

Agent-Based Models of Geographical Systems

Volumn , Issue , 2012, Pages 219-251

  Crooks, Andrew T ^a   Castle, Christian J E ^b  

^a GEORGE MASON UNIVERSITY   (United States)

^b MOTT MACDONALD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84955655056     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-90-481-8927-4_12     Document Type: Chapter

References (116)

1. Abdou, M., Hamill, L., & Gilbert, N. (2012). Designing and building an agent-based model. In A.J. Heppenstall, A.T. Crooks, L.M. See, & M. Batty (Eds.), Agent-based models of geographical systems (pp. 141-166). Dordrecht: Springer.
2. AgentLink. (2007). Software. Available at http://eprints.agentlink.org/view/type/software.html. Accessed on 12 July 2010.
3. AgentSheets. (2010). AgentSheets: The Sustainopolis model. Available at http://www.agentsheets. com/Applets/sustainopolis/. Accessed on 12 July 2010.
4. Andrade, P., Monteiro, A., & Camara, G. (2008). Entities and relations for agent-based modelling of complex spatial systems. BWSS 2008: 1st Brazilian Workshop on Social Simulation, Bahia.
5. AnyLogic. (2010). AnyLogic: Urban dynamics agent based model. Available at http://www.xjtek. com/anylogic/demo_models/48/. Accessed on 12 July 2010.
6. Armstrong, D. J. (2006). The quarks of object-oriented development. Communication of the ACM, 49(2), 123-128.
7. Axtell, R., Epstein, J. M., Dean, J. S., Gumerman, G. J., Swedlund, A. C., Harburger, J., Chakravarty, S., Hammond, R., Parker, J., & Parker, M. (2002). Population growth and collapse in a multiagent model of the Kayenta Anasazi in Long House Valley. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 99(3), 7275-7279.
8. Batty, M. (2005). Citiesandcomplexity: Understandingcitieswithcellularautomata, agent-based models, and fractals. Cambridge, MA: The MIT Press.
9. Batty, M., Conroy, R., Hillier, B., Jiang, B., Desyllas, J., Mottram, C., Penn, A., Smith, A., & Turner, A. (1998). The virtual tate, Working paper 5. London: Centre for Advanced Spatial Analysis (University College London).
10. Batty, M., Desyllas, J., & Duxbury, E. (2003). Safety in numbers? Modelling crowds and designing control for the Notting Hill carnival. Urban Studies, 40(8), 1573-1590.
11. Benenson, I., Aronovich, S., & Noam, S. (2005). Let’s talk objects: Generic methodology for urban high-resolution simulation. Computers, Environment and Urban Systems, 29(4), 425-453.
12. Benenson, I., Birfur, S., & Kharbash, V. (2006). Geographic automata systems and the OBEUS software for their implementation. In J. Portugali (Ed.), Complex artificial environments: Simulation, cognition and VR in the study and planning of cities (pp. 137-153). Berlin: Springer.
13. Berger, T., & Parker, D. C. (2001). Examples of specific research: Introduction to standard descriptions of projects’. In D. C. Parker, T. Berger, & S. M. Manson (Eds.), Meeting the Challenge of Complexity (pp. 48-54). Proceedings of a Special Workshop on Land-Use/Land-Cover Change, Irvine.
14. Bernard, L., & Krüger, T. (2000). Integration of GIS and spatio-temporal simulation models: Interoperable components for different simulation strategies. Transactions in GIS, 4(3), 197-215.
15. Berryman, M. (2008). Review ofsoftwareplatformsforagent basedmodels. Edinburgh: Defence Science and Technology Organisation, DSTO-GD-0532.
16. Booch, G. (1994). Object-oriented analysis and design with applications. Redwood City: Benjamin/Cummings.
17. Bousquet, F., Bakam, I., Proton, H., & Le Page, C. (1998). CORMAS: Common-pool resources and multi-agent systems. In A. P. Pobil, J. Mira, & A. Moonis (Eds.), Lecture notes in artificial intelligence 1416 (pp. 826-838). Berlin: Springer.
18. Brown, D. G. (2006). Agent-based models. In H. Geist (Ed.), The Earth’s changing land: An encyclopaedia of land-use and land-cover change (pp. 7-13). Westport: Greenwood Publishing Group.
19. Brown, D. G., Riolo, R., Robinson, D. T., North, M. J., & Rand, W. (2005). Spatial process and data models: Toward integration of agent-based models and GIS. Journal of Geographical Systems, 7(1), 25-47.
20. Carley, K. M. (1996). Validating computational models, Working Paper. Pittsburgh: Carnegie Mellon University.
21. Carvalho, J. (2000). Using agentSheets to teach simulation to undergraduate students. Journal of Artificial Societies and Social Simulation, 3(3). Available at http://jasss.soc.surrey.ac.uk/3/3/forum/2.html
22. Castle, C. J. E. (2007). Agent-based modelling of pedestrian evacuation: A study of London’s king’s cross underground station. Ph.D thesis, University College London, London.
23. Cioffi-Revilla, C. (2010). Computational social science. Wiley Interdisciplinary Reviews: Computational Statistics, 2(3), 259-271.
24. Cioffi-Revilla, C., Rogers, J. D., & Latek, M. (2010). The MASON householdWorlds of pastoral nomad societies. In K. Takadama, C. Cioffi-Revilla, & G. Deffaunt (Eds.), Simulating interacting agents and social phenomena: The second world congress in social simulation. Berlin: Springer.
25. Collier, N. T. (2010). Repast HPC manual. Available at http://repast.sourceforge.net/docs.html
26. Collier, N. T., & North, M. J. (2005). Repast for Python Scripting. Annual Conference of the North American Association for Computational Social and Organizational Science (NAACSOS), Notre Dame. Available at http://www.casos.cs.cmu.edu/events/conferences/2005/2005_ proceedings/Collier.pdf
27. Consequences Assessment Tool Set. (2011). Incident manager and first responder tools. Available at http://www.saic.com/products/security/cats/. Accessed on 12 Apr 2011.
28. Couclelis, H. (2001). Why I no longer work with agents: A challenge for ABMs of human-envi-ronment interactions. In D. C. Parker, T. Berger, & S. M. Manson (Eds.), Meeting the challenge of complexity (pp. 14-16). Proceedings of a Special Workshop on Land-Use/Land-Cover Change, Irvine.
29. Crooks, A. T. (2006). Exploring cities using agent-based models and GIS. In D. Sallach, C. M. Macal, & M. J. North (Eds.), Proceedings of the Agent 2006 Conference on Social Agents: Results and Prospects, University of Chicago and Argonne National Laboratory, Chicago. Available at http://agent2007.anl.gov/2006procpdf/Agent_2006.pdf
30. Crooks, A. T. (2007). The repast simulation/modelling system for geospatial simulation, Working Paper 123. London: Centre for Advanced Spatial Analysis (University College London).
31. Crooks, A. T. (2010). Constructing and implementing an agent-based model of residential segregation through vector GIS. International Journal of GIS, 24(5), 661-675.
32. Crooks, A. T., Castle, C. J. E., & Batty, M. (2008). Key challenges in agent-based modelling for geo-spatial simulation. Computer, Environment and Urban Systems, 32(6), 417-430.
33. Crooks, A.T., & Heppenstall, A.J. (2012), Introduction to agent-based modeling. In A.J. Heppenstall, A.T. Crooks, L.M. See, & M. Batty (Eds.), Agent-based models of geographical systems (pp. 85-105). Dordrecht: Springer.
34. Dugdale, J. (2004). An evaluation of seven software simulation tools for use in the social sciences. Available at http://www.irit.fr/COSI/training/evaluationoftools/Evaluation-Of-Simulation-Tools.htm. Accessed on 12 July 2010.
35. Epstein, J. M. (2009). Modelling to contain pandemics. Nature, 460, 687.
36. Fedra, K. (1996). Distributed models and embedded GIS: Integration strategies and case studies. In M. F. Goodchild, L. T. Steyaert, & B. O. Parks (Eds.), GIS and environmental modelling: Progress and research issues (pp. 413-417). Fort Collins: GIS World Books.
37. Filatova, T., Parker, D., & van der Veen, A. (2009). Agent-based urban land markets: Agent’s pricing behavior, land prices and urban land use change. Journal of Artificial Societies and Social Simulation, 12(1). Available at http://jasss.soc.surrey.ac.uk/12/1Z3.html
38. Fontaine, C. M., & Rounsevell, M. (2009). An agent-based approach to model future residential pressure on a regional landscape. Landscape Ecology, 24(9), 1237-1254.
39. GeoMASON. (2010). GIS integration for MASON. Available at https://mason.dev.java.net/source/browse/mason/contrib/geomason/. Accessed on 14 July 2010.
40. Gilbert, N. (2007). Agent-based models. London: Sage.
41. Gilbert, N., & Bankes, S. (2002). Platforms and methods for agent-based modelling. Proceeding of the National Academy of Sciences of the USA, 99(3), 7197-7198.
42. Gilbert, N., & Troitzsch, K. G. (2005). Simulation for the social scientist. Milton Keynes: Open University Press.
43. Goodchild, M. F. (2005). GIS, spatial analysis, and modelling overview. In D. J. Maguire, M. Batty, & M. F. Goodchild (Eds.), GIS, spatial analysis and modelling (pp. 1-18). Redlands: ESRI Press.
44. Graham, S., & Steiner, J. (2006). Travellersim: Growing settlement structures and territories with agent-based modelling. In J. T. Clark & E. M. Hagemeister (Eds.), Digital discovery: Exploring new frontiers in human heritage. Proceedings of the 34th Conference on Computer Applications and Quantitative Methods in Archaeology, Fargo.
45. Grimm, V., & Railsback, S. F. (2012). Designing, formulating and communicating agent-based models. In A. J. Heppenstall, A. T. Crooks, L. M. See, & M. Batty (Eds.) Agent-based models of geographical systems (pp. 361-377). Dordrecht: Springer.
46. Hailegiorgis, A. B. (2010). Changing residence in the city: An agent based model of residential mobility in Arlington County. The Association of American Geographers (AAG) Annual Meeting, Washington, DC, 14-18 Apr 2010.
47. Haklay, M., O’Sullivan, D., Thurstain-Goodwin, M., & Schelhorn, T. (2001). “So go downtown”: Simulating pedestrian movement in town centres. Environment and Planning B, 28(3), 343-359.
48. Harland, K., & Heppenstall, A. J. (2012). Using agent-based models for education planning: Is the UK education system agent-based. In A. J. Heppenstall, A. T. Crooks, L. M. See, & M. Batty (Eds.), Agent-based models of geographical systems (pp. 481-497). Dordrecht: Springer.
49. Hazard Prediction and Assessment Capability. (2004). Available at http://computing.ornl.gov/cse_home/hpac.shtml. Accessed on 12 Apr 2011.
50. Heywood, I., Cornelius, S., & Carver, S. (2006). An introduction to geographical information systems (3rd ed.). Harlow: Pearson Education.
51. Howe, T. R., Collier, N. T., North, M. J., Parker, M. T., & Vos, J. R. (2006). Containing agents: Contexts, projections, and agents. In D. Sallach, C. M. Macal, & M. J. North (Eds.), Proceedings of the Agent 2006 Conference on Social Agents: Results and Prospects, University of Chicago and Argonne National Laboratory, Chicago. Available at http://agent2007.anl.gov/2006procpdf/Agent_2006.pdf
52. Jackson, J., Forest, B., & Sengupta, R. (2008). Agent-based simulation of urban residential dynamics and land rent change in a gentrifying area of Boston. Transactions in GIS, 12(4), 475-491.
53. Janssen, M. A. (2009). Understanding artificial Anasazi. Journal of Artificial Societies and Social Simulation, 12(4). Available at http://jasss.soc.surrey.ac.uk/12/4Z13.html
54. Johnasson, A., & Kretz, T. (2012). Applied pedestrian modeling. In A. J. Heppenstall, A. T. Crooks, L. M. See, & M. Batty (Eds.), Agent-based models of geographical systems (pp. 451-462). Dordrecht: Springer.
55. Johnson, P. A., & Sieber, R. E. (2009). Agent-based modeling: A dynamic scenario planning approach to tourism PSS. In S. Geertman & J. Stillwell (Eds.), Planning support systems: Best practices and new methods (pp. 211-226). Berlin: Springer.
56. Kennedy, R. C., Lane, K. E., Fuentes, A., Hollocher, H., & Madey, G. (2009). Spatially aware agents: An effective and efficient use of GIS data within an agent-based model. Agent-Directed Simulation Symposium (ADS’09), San Diego, 22-27 Mar 2009.
57. Kennedy, W. B., Hailegiorgis, A. B., Rouleau, M., Bassett, J. K., Coletti, M., Balan, G. C., & Gulden, T. (2010). An agent-based model of conflict in East Africa and the effect of watering holes. Behavior Representation in Modeling and Simulation (BRiMS) Conference, Charleston.
58. Langran, G. (1992). Time in geographic information systems. London: Taylor & Francis.
59. Latek, M. M., Rizi, S. M. M., & Geller, A. (2010). Persistence in the political economy of conflict: The case of the Afghan Drug Industry. Complex Adaptive Systems: Resilience, Robustness, and Evolvability Workshop, Fall Symposium of Association for the Advancement of Artificial Intelligence, 11-13 Nov 2010, Arlington. Available at http://www.css.gmu.edu/projects/irregularwarfare/
60. Liebert, K. D., Earnest, D. C., & Tolk, A. (2008). Using GIS vector data to build virtual environments for agent based models. Proceedings of the 2008 Spring simulation multiconference (pp. 45-52), Ottawa.
61. Linthicum, D. S. (2000). Enterprise application integration. Boston: Addison-Wesley.
62. Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (2005). Geographical information systems and science (2nd ed.). New York: Wiley.
63. Luke, S., Cioffi-Revilla, C., Panait, L., & Sullivan, K. (2004). MASON: A new multi-agent simulation toolkit. SwarmFest 2004, Eighth Annual Swarm Users/Researchers Conference, University of Michigan, Ann Arbor. Available at http://www.cscs.umich.edu/swarmfest04/Program/PapersSlides/seanLuke-SwarmFest04-040507-2100.pdf
64. Luke, S., Cioffi-Revilla, C., Panait, L., Sullivan, K., & Balan, G. (2005). MASON: A multi-agent simulation environment. Simulation, 81(7), 517-527.
65. Maguire, D. J. (1995). Implementing spatial analysis and GIS applications for business and service planning. In P. A. Longley & G. Clarke (Eds.), GIS for business and service planning(pp. 171-191). Cambridge: GeoInformation International.
66. Maguire, D. J. (2005). Towards a GIS platform for spatial analysis and modelling. In D. J. Maguire, M. Batty, & M. F. Goodchild (Eds.), GIS, spatial analysis and modelling. Redlands: ESRI Press.
67. Makarov, V. L., Bakhtizin, A. R., & Zhitkov, V. A. (2008). Agent-based model for traffic jams in Moscow. ABS2 Agent Based Spatial Simulation International Workshop, 24-25 Nov 2008, Paris. Available at http://s4.csregistry.org/ABS2
68. Malleson, N. (2008). RepastCity - A demo virtual city. Available at http://portal.ncess.ac.uk/access/wiki/site/mass/repastcity.html. Accessed on 21 Jan 2009.
69. Malleson, N., Heppenstall, A., & See, L. (2010). Crime reduction through simulation: An agent-based model of burglary. Computers, Environment and Urban Systems, 34(3), 236-250.
70. MASON. (2010). Multi agent simulation of neighbourhood. Available at http://cs.gmu.edu/~eclab/projects/mason/. Accessed on 12 July 2010.
71. Mathevet, R., Bousquet, F., Le Page, C., & Antona, M. (2003). Agent-based simulations of interactions between duck population, farming decisions and leasing of hunting rights in the Camargue (Southern France). Ecological Modelling, 165(2-3), 107-126.
72. Minar, N., Burkhart, R., Langton, C. and Askenazi, M. (1996). The swarm simulation system: A toolkit for building multi-agent simulations. Available at http://www.santafe.edu/media/workingpapers/96-06-042.pdf. Accessed on 12 July 2010.
73. Mooij, W. M., Bennetts, R. E., Kitchens, W. M., & De Angelis, D. L. (2002). Exploring the effect of drought extent and interval on the Florida snail kite: Interplay between spatial and temporal scales. Ecological Modelling, 149(1-2), 25-39.
74. Najlis, R., Janssen, M. A., & Parker, D. C. (2001). Software tools and communication issues. In D. C. Parker, T. Berger, & S. M. Manson (Eds.), Meeting the Challenge of Complexity: Proceedings of a Special Workshop on Land-Use/Land-Cover Change (pp. 17-30), Irvine. Available at http://www.csiss.org/resources/maslucc/ABM-LUCC.pdf
75. NASA. (2010). World wind. Available at http://worldwind.arc.nasa.gov/java/. Accessed on 15 July 2010.
76. NatureServe Vista. (2011). Decision support for better planning, Available at http://www.natureserve.org/prodServices/vista/overview.jsp. Accessed on 12 Apr 2011.
77. NetLogo. (2010). NetLogo: Multi-agent programmable modelling environment. Available at http://ccl.northwestern.edu/netlogo/. Accessed on 12 July 2010.
78. Nikolai, C., & Madey, G. (2009). Tools of the trade: A survey of various agent based modeling platforms. Journal of Artificial Societies and Social Simulation, 12(2). Available at http://jasss. soc.surrey.ac.uk/12/2/2.html
79. North, M. J., & Macal, C. M. (2009). Foundations of and recent advances in artificial life modeling with Repast 3 and Repast Simphony. In A. Adamatzky & M. Komosinski (Eds.), Artificial life models in software (2nd ed., pp. 37-60). New York: Springer.
80. North, M. J., Howe, T. R., Collier, N. T., & Vos, J. R. (2005a). The Repast Simphony development environment. In C. M. Macal & M. J. North (Eds.), Proceedings of the Agent 2005 Conference on Generative Social Processes, Models, and Mechanisms, Chicago. Available at http://agent2007.anl.gov/Agent_2005.pdf
81. North, M. J., Howe, T. R., Collier, N. T., & Vos, J. R. (2005b). The Repast Simphony runtime system. In C. M. Macal, M. J. North, & D. Sallach (Eds.), Proceedings of the Agent 2005 Conference on Generative Social Processes, Models, and Mechanisms, Chicago. Available at http://agent2007.anl.gov/Agent_2005.pdf
82. OpenStarLogo. (2010). OpenStarLogo homepage. Available at http://education.mit.edu/openstarlogo/.Accessed on 12 July 2010.
83. Ozik, J. (2010). RELOGO getting started guide. Available at http://repast.sourceforge.net/docs/ReLogoGettingStarted.pdf
84. Parinov, S. I. (2007). New possibilities for simulations of socio-economic systems. Artificial Societies, 2(3-4): 23-53. Available at http://www.artsoc.ru/html_e/journal.htm
85. Parker, D. C. (2001). Object-orientated packages for agent-based modelling. Available at http://mason.gmu.edu/~dparker3/spat_abm/lectures/lecture2_tables.pdf Accessed on 12 June 2010.
86. Parker, D. C., Berger, T., & Manson, S. M. (2001). Proceedings of an International Workshop on Agent-Based Models of Land-Use and Land-Cover Change, Irvine. Available at http://www. csiss.org/maslucc/ABM-LUCC.htm
87. Peuquet, D. J. (2005). Time in GIS and geographical databases. In P. A. Longley, M. F. Goodchild, D. J. Maguire, & D. W. Rhind (Eds.), Geographical information systems: Principles, techniques, management and applications (Abridged Edition) (pp. 91-103). Hoboken: Wiley.
88. Peuquet, D. J., & Duan, N. (1995). An event-based spatio-temporal data model (ESTDM) for temporal analysis of geographic data. International Journal of Geographical Information Systems, 9(1), 2-24.
89. Pint, B., Crooks, A. T., & Geller, A. (2010). An agent-based model of organized crime: Favelas and the drug trade. 2nd Brazilian Workshop on Social Simulation, Sao Bernardo do Campo.
90. Railsback, S. F., & Harvey, B. C. (2002). Analysis of habitat selection rules using an individual-based model. Ecology, 83(7), 1817-1830.
91. Railsback, S. F., Lytinen, S. L., & Jackson, S. K. (2006). Agent-based simulation platforms: Review and development recommendations. Simulation, 82(9), 609-623.
92. Redlands Institute. (2010). What is agent analyst? Available at http://www.institute.redlands.edu/agentanalyst. Accessed on 12 July 2010.
93. Reitsma, F., & Albrecht, J. (2006). A process-oriented data model. In J. Drummond, R. Billen, D. Forrest, & E. Joao (Eds.), Dynamic and mobile GIS: Investigating change in space and time(pp. 77-87). London: Taylor & Francis.
94. Repast. (2011). Recursive porous agent simulation toolkit. Available at http://repast.sourceforge. net/. Accessed on 7 Mar 2011.
95. Repenning, A., & Ioannidou, A. (2004). Agent-based end-user development. Communications of the Association of Computing Machinery, 47(9), 43-46.
96. Repenning, A., Ioannidou, A., & Zola, J. (2000). AgentSheets: End-user programmable simulations. Journal of Artificial Societies and Social Simulation, 3(3). Available at http://jasss.soc. surrey.ac.uk/3/3/forum/1.html.
97. Rixon, A., Moglia, M., & Burn, S. (2005). Bottom-up approaches to building agent-based models: Discussing the need for a platform. Proceedings of the Joint Conference on Multi-Agent Modelling for Environmental Management, Bourg-St-Maurice.
98. Robertson, D. A. (2005). Agent-based modeling toolkits. Academy of Management Learning and Education, 4(4), 525-527.
99. Schelhorn, T., O’Sullivan, D., Haklay, M., & Thurstain-Goodwin, M. (1999). STREETS: An agent-based pedestrian model, Working paper. London: Centre for Advanced Spatial Analysis (University College London).
100. Serenko, A., & Detlor, B. (2002). Agent toolkits: A general overview of the market and an assessment of instructor satisfaction with utilizing toolkits in the classroom, Working Paper 455. Hamilton: McMaster University (School of Business). Available at http://merc.mcmaster.ca/wpapers/wpaper455.html
101. Sondheim, M., Gardels, K., & Buehler, K. (2005). GIS interoperability. In P. A. Longley, M. F. Goodchild, D. J. Maguire, & D. W. Rhind (Eds.), Geographical information systems: Principles, techniques, management and applications (Abridged Edition) (pp. 347-358). Hoboken: Wiley.
102. Swarm. (2010). Swarm: A platform for agent-based models. Available at http://www.swarm.org/. Accessed on 12 July 2010.
103. SwarmWiki. (2010). Tools for Agent-Based Modelling. Available at http://www.swarm.org/wiki/Tools_for_Agent-Based_Modelling. Accessed on 12 July 2010.
104. Tatara, E., North, M. J., Howe, T. R., Collier, N. T., & Vos, J. R. (2006). An introduction to repast simphony modelling using a simple predator-prey example. In D. Sallach, C. M. Macal, & M. J. North (Eds.), Proceedings of the Agent 2006 Conference on Social Agents: Results and Prospects, University of Chicago and Argonne National Laboratory, Chicago. Available at http://agent2007.anl.gov/2006procpdf/Agent_2006.pdf
105. Tesfatsion, L. (2010). General software and toolkits. Available at http://www.econ.iastate.edu/tesfatsi/acecode.htm. Accessed on 12 July 2010.
106. Tesfatsion, L., & Judd, K. L. (Eds.). (2006). Handbook of computational economics: Agent-based computational economics (Vol. 2). Amsterdam: North-Holland.
107. Tobias, R., & Hofmann, C. (2004). Evaluation of free java-libraries for social-scientific agent based simulation. Journal of Artificial Societies and Social Simulation, 7(1). Available at http://jasss.soc.surrey.ac.uk/7/1/6.html
108. Torrens, P. M. (2009). Process models and next-generation geographic information technology (GIS best practices: Essays on geography and GIS, Vol. 2, pp. 63-75). Redlands: ESRI Press.
109. Torrens, P. M., & Nara, A. (2007). Modelling gentrification dynamics: A hybrid approach. Computers, Environment and Urban Systems, 31(3), 337-361.
110. Ungerer, M. J., & Goodchild, M. F. (2002). Integrating spatial data analysis and GIS: A new implementation using component object model (COM). International Journal of Geographic Information Science, 16(1), 41-53.
111. Vos, J. R. (2005). Repast.NET: The Repast framework implemented in the.NET. Annual Conference of the North American Association for Computational Social and Organizational Science (NAACSOS), Notre Dame. Available at http://www.casos.cs.cmu.edu/events/conferences/2005/2005_proceedings/Vos.pdf
112. Wegener, M. (2000). Spatial models and GIS. In A. S. Fotheringham & M. Wegener (Eds.), Spatial models and GIS: New potential and new models (pp. 3-20). London: Taylor & Francis.
113. Westervelt, J. D. (2002). Geographic information systems and agent-based modelling. In H. R. Gimblett (Ed.), Integrating geographic information systems and agent-based modelling techniques for simulating social and ecological processes (pp. 83-104). Oxford: Oxford University Press.
114. Wikipedia. (2010). Comparison of agent-based modeling software. Available at http://en.wikipedia. org/wiki/Comparison_of_agent-based_modeling_software. Accessed on 12 July 2010.
115. Wilensky, U. (2006). NetLogo grand canyon model. Available at http://ccl.northwestern.edu/netlogo/models/GrandCanyon. Accessed on 15 July 2010.
116. Zeiler, M. (1999). Modelling ourworld: TheESRIguide to geodatabase design. Redlands: ESRI Press.