Abstract
Operational optimization models of technology adoptions commonly assume the existence of a social planner who knows a long-term future. Such kind of planner does not exist in reality. This paper introduces a simulation model in which an intelligent agent forms its expectation on future by continuous learning from its previous experience, and adjusts its decision on technology development continuously. Simulations with the model show that with the intelligent agent, an advanced but currently expensive technology will be adopted, but with a much slower pace than in optimization models.
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References
Messner, S.: Endogenised technological learning in an energy systems model. Journal of Evolutionary Economics 7, 291–313 (1997)
Kypreos, S., Barreto, L., Capros, P., Messner, S.: ERIS: A model prototype with endogenous technological change. International Journal of Global Energy 14, 374–397 (2000)
Gritsevskyi, A., Nakicenovic, N.: Modeling uncertainty of induced technological change. Energy Policy 28, 907–921 (2000)
Ma, T.: An agent-based model of endogenous technological change – an extension to the Grübler-Gritsvskyi model, report no. IR-06-044, International Institute for Applied Systems Analysis, Laxenburg, Austria (2006)
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© 2009 Springer-Verlag Berlin Heidelberg
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Ma, T., Chi, C., Chen, J., Shi, Y. (2009). A Simulation Model of Technological Adoption with an Intelligent Agent. In: Shi, Y., Wang, S., Peng, Y., Li, J., Zeng, Y. (eds) Cutting-Edge Research Topics on Multiple Criteria Decision Making. MCDM 2009. Communications in Computer and Information Science, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02298-2_29
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DOI: https://doi.org/10.1007/978-3-642-02298-2_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02297-5
Online ISBN: 978-3-642-02298-2
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