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Qualitative Modeling and Simulation of Socio-Economic Phenomena

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Abstract

This paper describes an application of recently developed qualitative reasoning techniques to complex, socio-economic allocation problems. We explain why we believe traditional optimization methods are inappropriate and how qualitative reasoning could overcome some of these shortcomings. A case study is presented where an authority is expected to devise a policy that satisfies certain constraints. We describe how sets of rules of thumb implementing such a policy can be analyzed and validated by the decision maker using a program which automatically builds and simulates qualitative models of the underlying dynamical system. Such a program constructs and simulates models from incomplete descriptions of initial states and functional relationships between variables. We show that it nevertheless gives sufficient information to the decision maker.

Suggested Citation

  • Giorgio Brajnik & Marji Lines, 1998. "Qualitative Modeling and Simulation of Socio-Economic Phenomena," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 1(1), pages 1-2.
  • Handle: RePEc:jas:jasssj:1997-6-1
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    1. Farley, Arthur M. & Lin, Kuan-Pin, 1990. "Qualitative reasoning in economics," Journal of Economic Dynamics and Control, Elsevier, vol. 14(2), pages 465-490, May.
    2. Lane, David A, 1993. "Artificial Worlds and Economics, Part I," Journal of Evolutionary Economics, Springer, vol. 3(2), pages 89-107, May.
    3. Hope, Chris & Anderson, John & Wenman, Paul, 1993. "Policy analysis of the greenhouse effect : An application of the PAGE model," Energy Policy, Elsevier, vol. 21(3), pages 327-338, March.
    4. Dowlatabadi, Hadi & Morgan, M. Granger, 1993. "A model framework for integrated studies of the climate problem," Energy Policy, Elsevier, vol. 21(3), pages 209-221, March.
    5. Lane, David A, 1993. "Artificial Worlds and Economics, Part II," Journal of Evolutionary Economics, Springer, vol. 3(3), pages 177-197, August.
    6. Marian Leimbach, 1996. "Development of a Fuzzy optimization model, supporting global warming decision-making," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 7(2), pages 163-192, March.
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    Cited by:

    1. Gelman, Irit Askira, 2005. "Addressing time-scale differences among decision-makers through model abstractions," European Journal of Operational Research, Elsevier, vol. 160(2), pages 325-335, January.

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