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Evolving Optimal Spatial Allocation Policies for Complex and Uncertain Environments

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Agents and Artificial Intelligence (ICAART 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 449))

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Abstract

Urban green spaces play a crucial role in the creation of healthy environments in densely populated areas. Agent-based systems are commonly used to model processes such as green-space allocation. In some cases, this systems delegate their spatial assignation to optimisation techniques to find optimal solutions. However, the computational time complexity and the uncertainty linked with long-term plans limit their use. In this paper we explore an approach that makes use of a statistical model which emulates the agent-based system’s behaviour based on a limited number of prior simulations to inform a Genetic Algorithm.

The approach is tested on a urban growth simulation, in which the overall goal is to find policies that maximise the inhabitants’ satisfaction. We find that the model-driven approximation is effective at leading the evolutionary algorithm towards optimal policies.

This paper is a revised and extended version of a previous publication [1] reported in the Proceedings of the 5th International Conference on Agents and Artificial Intelligence. The key additions cover: Sects. 3 and 4 improvement of the complexity of non-urban cells prices and its inclusion as a new source of uncertainty. In Sect. 5, a new heuristic is studied to enrich the comparison phase. Finally in Sect. 6 more experimental results and comparative evaluations are performed.

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References

  1. Vallejo, M., Corne, D.W., Rieser, V.: Evolving urbanisation policies - using a statistical model to accelerate optimisation over agent-based simulations. In: ICAART 2013–5th Conference on Agents and Artificial Intelligence, pp. 1–11 (2013)

    Google Scholar 

  2. Forsyth, A., Mussachio, L.: Designing Small Parks: A Manual for Addressing Social and Ecological Concerns. Wiley, New York (2005)

    Google Scholar 

  3. Parker, D.C., Hoffmann, M.J., Deadman, P., Parker, D.C., Manson, S.M., Manson, S.M., Janssen, M.A., Janssen, M.A.: Multi-agent systems for the simulation of land-use and land-cover change: a review. Ann. Assoc. Am. Geogr. 93, 314–337 (2003)

    Article  Google Scholar 

  4. Sasaki, Y., Box, P.: Agent-based verification of von thünen’s location theory. J. Artif. Soc. Soc. Simul., 6 (2003)

    Google Scholar 

  5. Sanders, L., Pumain, D., Mathian, H., Gurin-Pace, F., Bura, S.: Simpop: a multiagent system for the study of urbanism. Environ. Plann. B Plann. Des. 24, 287–305 (1997)

    Article  Google Scholar 

  6. Robinson, D., Murray-Rust, D., Rieser, V., Milicic, V., Rounsevell, M.: Modelling the impacts of land system dynamics on human well-being: using an agent-based approach to cope with data limitations in koper, slovenia. Comput. Environ. Urban Syst. (Special Issue: Geoinformatics) 2010(36), 164–176 (2012)

    Article  Google Scholar 

  7. Rieser, V., Lemon, O.: Reinforcement Learning for Adaptive Dialogue Systems: A Data-driven Methodology for Dialogue Management and Natural Language Generation. Theory and Applications of Natural Language Processing. Springer, Heidelberg (2011)

    Book  Google Scholar 

  8. Vallejo, M., Vargas, P., Corne, D.: A fast approximative approach for the vehicle routing problem. In: 2012 12th UK Workshop on Computational Intelligence (UKCI), pp. 1–8 (2012)

    Google Scholar 

  9. Costanza, R., d’Arge, R., de Groot, R., Farber, S., Grasso, M., Hannon, B., Limburg, K., Naeem, S., O’Neill, R., Paruelo, J., Raskin, R., Sutton, P., van den Belt, M.: The value of the world’s ecosystem services and natural capital. Ecol. Econ. 25, 3–15 (1998)

    Article  Google Scholar 

  10. Nowak, D., McPherson, E.: Quantifying the impact of trees: the chicago urban forest climate project. Unasylva 44, 39–44 (1993)

    Google Scholar 

  11. Newmann, J.V.: Theory of Self-Reproducing Automata. University of Illinois Press, Urbana (1966). (edited by Burks, A.W.)

    Google Scholar 

  12. Otter, H.S., van der Veen, A., de Vriend, H.J.: Abloom: location behaviour, spatial patterns, and agent-based modelling. J. Artif. Soc. Soc. Simul. 4, 1147–1152 (2001)

    Google Scholar 

  13. Brown, D.G., Robinson, D.T.: Effects of heterogeneity in residential preferences on an agent-based model of urban sprawl. Ecol. Soc. 11, 46 (2006)

    Google Scholar 

  14. Devisch, O., Timmermans, H., Arentze, T., Borgers, A.: An agent-based model of residential choice dynamics in nonstationary housing markets. Environ. Plann. A 41, 1997–2013 (2009)

    Article  Google Scholar 

  15. Parker, D.C., Filatova, T.: A conceptual design for a bilateral agent-based land market with heterogeneous economic agents. Comput. Environ. Urban Syst. 32, 454–463 (2008). (GeoComputation: Modeling with spatial agents)

    Article  Google Scholar 

  16. Filatova, T., Parker, D., van der Veen, A.: Agent-based urban land markets: agentś pricing behavior, land prices and urban land use change. J. Artif. Soc. Soc. Simul. 12, 3 (2009)

    Google Scholar 

  17. Miller, E.J., Hunt, J.D., Abraham, J.E., Salvini, P.A.: Microsimulating urban systems. Comput. Environ. Urban Syst. 28, 9–44 (2004)

    Article  Google Scholar 

  18. Holland, J.: Adaptation in Natural and Artificial Systems. The University of Michigan Press, Ann Arbor (1975)

    Google Scholar 

  19. Darwin, C.: On the Origin of Species by Means of Natural Selections: or the Preservation of Favoured Races in the Struggle for Life. Murray, London (1861)

    Google Scholar 

  20. Pukkala, T., Kurttila, M.: Examining the performance of six heuristic optimisation techniques in different forest planning problems. Silva Fennica 39, 67–80 (2005)

    Google Scholar 

  21. Lu, F., Eriksson, L.O.: Formation of harvest units with genetic algorithms. For. Ecol. Manag. 130, 57–67 (2000)

    Article  Google Scholar 

  22. Wu, J., Zheng, C., Chien, C.C., Zheng, L.: A comparative study of monte carlo simple genetic algorithm and noisy genetic algorithm for cost-effective sampling network design under uncertainty. Adv. Water Resour. 29, 899–911 (2006)

    Article  Google Scholar 

  23. Rieser, V., Robinson, D.T., Murray-Rust, D., Rounsevell, M.: A comparison of genetic algorithms and reinforcement learning for optimising sustainable forest management. In: GeoComputation (2011)

    Google Scholar 

  24. Qin, X., Huang, G., Liu, L.: A genetic-algorithm-aided stochastic optimization model for regional air quality management under uncertainty. J. Air Waste Manag. Assoc. 60, 63–71 (2010)

    Article  Google Scholar 

  25. Wang, N., Yang, Y.: Target geometry matching problem for hybrid genetic algorithm used to design structures subjected to uncertainty. In: IEEE Congress on Evolutionary Computation, CEC ’09, pp. 1644–1651 (2009)

    Google Scholar 

  26. Wang, N., Zhang, X., Yang, Y.: A hybrid genetic algorithm for constrained multi-objective optimization under uncertainty and target matching problems. Appl. Soft Comput. 13, 3636–3645 (2013)

    Article  Google Scholar 

  27. Alonso, W.: Location and Land Use. Publications of the Joint Center for Urban Studies. Harvard University Press, Cambridge (1964)

    Book  Google Scholar 

  28. Byomkesh, T., Nakagoshi, N., Dewan, A.: Urbanization and green space dynamics in greater dhaka, bangladesh. Landscape and Ecological Engineering, pp. 1–14 (2010). doi:10.1007/s11355-010-0147-7

  29. Passow, S.S.: Land reserves and teamwork in planning stockholm. J. Am. Inst. Plan. 36, 179–188 (1970)

    Article  Google Scholar 

  30. Giles-Corti, B., Broomhall, M.H., Knuiman, M., Collins, C., Douglas, K., Ng, K., Lange, A., Donovan, R.J.: Increasing walking: how important is distance to, attractiveness, and size of public open space? Am. J. Prev. Med. 28, 169–176 (2005). (Active Living Research)

    Article  Google Scholar 

  31. Plantinga, A.J., Lubowski, R.N., Stavins, R.N.: The effects of potential land development on agricultural land prices. J. Urban Econ. 52, 561–581 (2002)

    Article  Google Scholar 

  32. Riley, C.: Comments on mills & evans. In: Proceedings of seminar on Land Use Regulation, Lincoln Institute for Land Policy, Cambridge Mass (2002)

    Google Scholar 

  33. Tyrväinen, L., Miettinen, A.: Property prices and urban forest amenities. J. Environ. Econ. Manage. 39, 205–223 (2000)

    Article  MATH  Google Scholar 

  34. Thorsnes, P.: The value of a suburban forest preserve: estimates from sales of vacant residential building lots. Land Econ. 78, 426–441 (2002)

    Article  Google Scholar 

  35. Goldberg, D.E.: A note on boltzmann tournament selection for genetic algorithms and population-oriented simulated annealing. Complex Syst. 4, 445–460 (1990)

    MATH  Google Scholar 

  36. Wilson, S.W.: Classifier fitness based on accuracy. Evol. Comput. 3, 149–175 (1995)

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, UK

    Marta Vallejo, David W. Corne & Verena Rieser

Authors
  1. Marta Vallejo
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  2. David W. Corne
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  3. Verena Rieser
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Corresponding author

Correspondence to Marta Vallejo .

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Editors and Affiliations

  1. INSTICC, Setúbal, Portugal

    Joaquim Filipe

  2. Instituto de Telecomunicações, Lisbon, Portugal

    Ana Fred

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Vallejo, M., Corne, D.W., Rieser, V. (2014). Evolving Optimal Spatial Allocation Policies for Complex and Uncertain Environments. In: Filipe, J., Fred, A. (eds) Agents and Artificial Intelligence. ICAART 2013. Communications in Computer and Information Science, vol 449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44440-5_21

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  • DOI: https://doi.org/10.1007/978-3-662-44440-5_21

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  • Print ISBN: 978-3-662-44439-9

  • Online ISBN: 978-3-662-44440-5

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