An intelligent spatial land use planning support system using socially rational agents

References

• Abolhasani, S., et al., 2016. Simulating urban growth under planning policies through parcel-based cellular automata (ParCA) model. International Journal of Geographical Information Science, 30 (11), 1–26.
   Web of Science ®Google Scholar
• Alsrheed, F., et al., 2014. Intelligent agents for automated cloud computing negotiation. In: ed. 2014 international conference on Multimedia Computing and Systems (ICMCS), 1169–1174.
   Google Scholar
• An, L., 2012. Modeling human decisions in coupled human and natural systems: review of agent-based models. Ecological Modelling, 229, 25–36. doi:10.1016/j.ecolmodel.2011.07.010
   Web of Science ®Google Scholar
• Arciniegas, G., Janssen, R., and Omtzigt, N., 2011. Map-based multicriteria analysis to support interactive land use allocation. International Journal of Geographical Information Science, 25 (12), 1931–1947. doi:10.1080/13658816.2011.556118
   Web of Science ®Google Scholar
• Arentze, T.A., et al., 2010. An agent-based heuristic method for generating land-use plans in urban planning. Environment and Planning. B, Planning & Design, 37 (3), 463. doi:10.1068/b35050
   Web of Science ®Google Scholar
• Arentze, T.A., 2013. Adaptive personalized travel information systems: a Bayesian method to learn users’ personal preferences in multimodal transport networks. Intelligent Transportation Systems, IEEE Transactions On, 14 (4), 1957–1966. doi:10.1109/TITS.2013.2270358
   Web of Science ®Google Scholar
• Arentze, T.A., 2015. Individuals’ social preferences in joint activity location choice: a negotiation model and empirical evidence. Journal of Transport Geography, 48, 76–84. doi:10.1016/j.jtrangeo.2015.08.018
   Web of Science ®Google Scholar
• Baarslag, T., et al., 2015. Learning about the opponent in automated bilateral negotiation: a comprehensive survey of opponent modeling techniques. Autonomous Agents and Multi-Agent Systems, 30 (5), 849–898.
   Web of Science ®Google Scholar
• Becu, N., et al., 2008. Participatory computer simulation to support collective decision-making: potential and limits of stakeholder involvement. Land Use Policy, 25 (4), 498–509. doi:10.1016/j.landusepol.2007.11.002
   Web of Science ®Google Scholar
• Biermann, S., 2011. Planning support systems in a multi-dualistic spatial planning context. Journal of Urban Technology, 18 (4), 5–37. doi:10.1080/10630732.2011.648432
   Web of Science ®Google Scholar
• Bogaert, S., Boone, C., and Declerck, C., 2008. Social value orientation and cooperation in social dilemmas: a review and conceptual model. British Journal of Social Psychology, 47 (3), 453–480. doi:10.1348/014466607X244970
   PubMed Web of Science ®Google Scholar
• Bone, C. and Dragićević, S., 2010. Simulation and validation of a reinforcement learning agent-based model for multi-stakeholder forest management. Computers, Environment and Urban Systems, 34 (2), 162–174. doi:10.1016/j.compenvurbsys.2009.10.001
   Web of Science ®Google Scholar
• Bousquet, F., et al., 2002. Multi-agent systems and role games: collective learning processes for ecosystem management. In:  M.A. Janssen, ed. Complexity and ecosystem management: The theory and practice of multi-agent systems. Cheltenham: Edward Elgar Publishing, 248–285.
   Google Scholar
• Braziunas, D. and Boutilier, C., 2009. Elicitation of factored utilities. AI Magazine, 29 (4), 79.
   Web of Science ®Google Scholar
• Buffett, S. and Spencer, B., 2007. A Bayesian classifier for learning opponents’ preferences in multi-object automated negotiation. Electronic Commerce Research and Applications, 6 (3), 274–284. doi:10.1016/j.elerap.2006.06.008
   Web of Science ®Google Scholar
• Castella, J.-C., Trung, T.N., and Boissau, S., 2005. Participatory simulation of land-use changes in the northern mountains of Vietnam: the combined use of an agent-based model, a role-playing game, and a geographic information system. Ecology and Society, 10 (1), 27. doi:10.5751/ES-01328-100127
   Web of Science ®Google Scholar
• Chen, L. and Pu, P., 2004. Survey of preference elicitation methods. Lausanne: Swiss Federal Institute of Technology.
   Google Scholar
• Chen, Y., et al., 2010. An agent-based model for optimal land allocation (AgentLA) with a contiguity constraint. International Journal of Geographical Information Science, 24 (8), 1269–1288. doi:10.1080/13658810903401024
   Web of Science ®Google Scholar
• Cheng, K.L., 2014. Agent modeling in stochastic repeated games. Thesis (PhD). University of Maryland.
   Google Scholar
• Couclelis, H., 2005. “Where has the future gone?” Rethinking the role of integrated land-use models in spatial planning. Environment and Planning A, 37 (8), 1353–1371. doi:10.1068/a3785
   Web of Science ®Google Scholar
• Dostatni, E., et al., 2015. Multi-agent system to support decision-making process in ecodesign. In: 10th International Conference on Soft Computing Models in Industrial and Environmental Applications, Burgos, 463–474.
   Google Scholar
• Ferrand, N., 1996. Modelling and supporting multi-actor spatial planning using multi-agents systems. In: Third International Conference Integrating GIS and Environmental Modeling, Santa Fe, NM.
   Google Scholar
• Filatova, T., et al., 2013. Spatial agent-based models for socio-ecological systems: challenges and prospects. Environmental Modelling & Software, 45, 1–7. doi:10.1016/j.envsoft.2013.03.017
   Web of Science ®Google Scholar
• Gaber, J. and Gaber, S.L., 2010. Using face validity to recognize empirical community observations. Evaluation and Program Planning, 33 (2), 138–146. doi:10.1016/j.evalprogplan.2009.08.001
   PubMed Web of Science ®Google Scholar
• Geertman, S. and Stillwell, J., 2012. Planning support systems in practice. Utrecht: Springer Science & Business Media.
   Google Scholar
• Ghavami, S.M. and Talaei, M., 2017. Towards a conceptual multi-agent based framework for simulating spatial-group decision making process. Journal of Geographical Systems, 19, 1.
   Web of Science ®Google Scholar
• Ghavami, S.M., Taleai, M., and Arentze, T., 2016. Socially rational agents in spatial land use planning: a heuristic proposal based negotiation mechanism. Computers, Environment and Urban Systems, 60, 67–78. doi:10.1016/j.compenvurbsys.2016.08.004
   Web of Science ®Google Scholar
• Google Map. 2016. [online]. Available from: https://www.google.com/maps/place/Zanjan,+Iran/@36.681,48.4231825,12z/data=!3m1!4b1!4m2!3m1!1s0x3ff610adb062ed93:0xab4ea9398b48690 [Accessed 29 Mar 2016].
   Google Scholar
• Ive, J., 1992. LUPIS: computer assistance for land-use allocation. Resource Technology, 92, 16–18.
   Google Scholar
• Kersten, G.E. and Lai, H., 2007. Negotiation support and e-negotiation systems: an overview. Group Decision and Negotiation, 16 (6), 553–586. doi:10.1007/s10726-007-9095-5
   Web of Science ®Google Scholar
• Klosterman, R.E., 1999. The what if? Collaborative planning support system. Environment and planning b: Planning and design, 26 (3), 393–408. doi:10.1068/b260393
   Web of Science ®Google Scholar
• Kollock, P., 1998. Social dilemmas: the anatomy of cooperation. Annual Review of Sociology, 183–214. doi:10.1146/annurev.soc.24.1.183
   Web of Science ®Google Scholar
• Ligtenberg, A., et al., 2004. A design and application of a multi-agent system for simulation of multi-actor spatial planning. Journal of Environmental Management, 72 (1), 43–55. doi:10.1016/j.jenvman.2004.02.007
   PubMed Web of Science ®Google Scholar
• Ligtenberg, A., et al., 2009. Simulating knowledge sharing in spatial planning: an agent-based approach. Environment and Planning B: Planning and Design, 36 (4), 644. doi:10.1068/b33059
   Web of Science ®Google Scholar
• Long, Y. and Zhang, Y., 2015. Land-use pattern scenario analysis using planner agents. Environment and Planning B: Planning and Design, 42 (4), 615–637.
   Web of Science ®Google Scholar
• Ma, L., et al., 2007. Modelling land-use decisions under conditions of uncertainty. Computers, Environment and Urban Systems, 31 (4), 461–476. doi:10.1016/j.compenvurbsys.2007.02.002
   Web of Science ®Google Scholar
• Parker, D.C., et al., 2003. Multi-agent systems for the simulation of land-use and land-cover change: a review. Annals of the Association of American Geographers, 93 (2), 314–337. doi:10.1111/1467-8306.9302004
   Web of Science ®Google Scholar
• Pooyandeh, M. and Marceau, D.J., 2013. A spatial web/agent-based model to support stakeholders’ negotiation regarding land development. Journal of Environmental Management, 129, 309–323. doi:10.1016/j.jenvman.2013.07.028
   PubMed Web of Science ®Google Scholar
• Pooyandeh, M. and Marceau, D.J., 2014. Incorporating Bayesian learning in agent-based simulation of stakeholders’ negotiation. Computers, Environment and Urban Systems, 48, 73–85. doi:10.1016/j.compenvurbsys.2014.07.003
   Web of Science ®Google Scholar
• Recatalá, L., et al., 2000. Land-use planning in the Valencian Mediterranean region: using LUPIS to generate issue relevant plans. Journal of Environmental Management, 59 (3), 169–184. doi:10.1006/jema.2000.0350
   Web of Science ®Google Scholar
• Rossi, P.E., Allenby, G.M., and McCulloch, R., 2012. Bayesian statistics and marketing. Hoboken, NJ: John Wiley & Sons.
   Google Scholar
• Saarloos, D., et al., 2005. A multiagent model for alternative plan generation. Environment and Planning B: Planning and Design, 32 (4), 505–522. doi:10.1068/b31120
   Web of Science ®Google Scholar
• Sim, K.M., Guo, Y., and Shi, B., 2009. BLGAN: Bayesian learning and genetic algorithm for supporting negotiation with incomplete information. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 39 (1), 198–211. doi:10.1109/TSMCB.2008.2004501
   PubMed Web of Science ®Google Scholar
• Statistical Center of Iran, 2012. Iran statistical yearbook. Tehran, Iran: Iranian Mangement Organisation.
   Google Scholar
• Tan, S., et al., 2015. A hybrid mathematical model for urban land-use planning in association with environmental–ecological consideration under uncertainty. Environment and Planning B: Planning and Design, 5, 1–26.
   Google Scholar
• Vahidov, R., Kersten, G., and Saade, R., 2014. An experimental study of software agent negotiations with humans. Decision Support Systems, 66, 135–145. doi:10.1016/j.dss.2014.06.009
   Web of Science ®Google Scholar
• Van Lange, P.A.M., et al., 2013. The psychology of social dilemmas: a review. Organizational Behavior and Human Decision Processes, 120 (2), 125–141. doi:10.1016/j.obhdp.2012.11.003
   Web of Science ®Google Scholar
• Von Neumann, J. and Morgenstern, O., 2007. Theory of games and economic behavior. Princeton, NJ: Princeton university press.
   Google Scholar
• Wang, H., Shen, Q., and Tang, B.S., 2014. A review of planning support systems for urban land use planning. In: Proceedings of the 17th International Symposium on Advancement of Construction Management and Real Estate, Heidelberg, 233–248.
   Google Scholar
• Yuan, C., and Druzdzel, M. J. 2006. Importance sampling algorithms for bayesian networks: principles and performance. Mathematical and Computer Modelling, 43(9), 1189–1207. doi:10.1016/j.mcm.2005.05.020
   Google Scholar