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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 305))

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Abstract

Comparing with other sciences, the quantitative success of economic science is disappointing. People fly to the moon, the touch of a simple button can destroy more than half of the world and energy is extracted with the speed of light. During all these developments of science the economic achievements are somewhere near zero. The economists can praise however with the recurrent inability to predict and revaluate the crises and with the ability to create financial innovations. This study aims to present the benefits of the multi agent (MAS) models in the economy. In order to do that this paper intends to demonstrate the need of such models today. Furthermoreare presented some attempts of using multi agent models and concluding with the idea that the economy needs a scientific revolution, and this can be done using multi criteria or multi agent models.

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References

  1. Lauterbach, B., Schultz, P.: Pricing warrants: An empirical study of the Black-Scholes Model and its alternative. The Journal of Finance XLV(4), 1181–1209 (1990)

    Article  Google Scholar 

  2. Allen, F.: Liquidity and crises, p. 78. Oxford University Press (2011)

    Google Scholar 

  3. Stiglitz, J.: Pareto efficient and optimal taxation and the new welfare economics, National Bureau of Economic Research, Cambridge, Working Paper 2189 (1987)

    Google Scholar 

  4. Allen, F., Gale, D.: Understanding financial crises. Clarendon Lectures in Finance. Oxford University Press, Oxford (2009)

    Google Scholar 

  5. Taylor, J.B.: The financial crisis and the policy responses: An empirical analysis of what went wrong, Cambridge, NBER Working Paper No. 14631 (2009)

    Google Scholar 

  6. Zopounidis, C., Pardalos, P.M. (eds.): Handbook of Multicriteria Analysis, Applied Optimization, vol. 103. Springer, Heidelberg (2010), doi:10.1007/978-3-540-92828-7_2

    Google Scholar 

  7. LeBaron, B.: Evolution and time horizons in an agent based stock market. Macroeconomic Dyn. 5(2), 225–254 (2001)

    Article  MATH  Google Scholar 

  8. Stiglitz, J.E., Gallegati, M.: Heterogeneous Interacting Agent Models for Understanding Monetary Economies. Eastern Economic Journal 37, 6–12 (2011)

    Article  Google Scholar 

  9. Tampu, D.L., Costea, C.: A Concerning View In The Liquidity Crisis Through The Game Theory. Journal of Information Systems and Operations Management 6(1), 175–184 (2012)

    Google Scholar 

  10. LeBaron, B., Arthur, W.B., Palmer, R.: Time series properties of an artificial stock market. J. Economic Dyn. Control 23(9-10), 1487–1516 (1999)

    Article  MATH  Google Scholar 

  11. LeBaron, B.: Agent-based computational finance: Suggested readings and early research. Journal of Economic Dynamics and Control 24(5-7), 679–702 (2000)

    Article  MATH  Google Scholar 

  12. Battiston, S., Delli Gatti, D., Gallegati, M., Greenwald, B., Stiglitz, J.E.: Credit Chains and Bankruptcies Avalanches in Production Networks. Journal of Economic Dynamics and Control 31, 2061–2084 (2007)

    Article  MATH  Google Scholar 

  13. Raberto, M., Cincotti, S.: Multi-agent modeling and simulation of a sequential monetary production economy. t Computing in Economics and Finance, p. 260. Society for Computational Economics (2004)

    Google Scholar 

  14. Costea, C.: Application of Tuncay’s Language Teacher Model to Business-Customer Relations. International Journal of Modern Physics C 19(02), 267–270

    Google Scholar 

  15. Vasile, A., Costea, C.-E., Viciu, T.-G.: An Evolutionary Game Theory Approach to Market Competition and Cooperation. Advs. Complex Syst. 15, 1250044, 15 (2012), doi:10.1142/S0219525912500440

    Article  MathSciNet  Google Scholar 

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Correspondence to Carmen Costea .

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Costea, C., Tâmpu, D. (2013). The MAS Models Use – An Imperative Approach to Build a New Economic Paradigm. In: Ventre, A., Maturo, A., Hošková-Mayerová, Š., Kacprzyk, J. (eds) Multicriteria and Multiagent Decision Making with Applications to Economics and Social Sciences. Studies in Fuzziness and Soft Computing, vol 305. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35635-3_6

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  • DOI: https://doi.org/10.1007/978-3-642-35635-3_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35634-6

  • Online ISBN: 978-3-642-35635-3

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