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Quantum Approach Explains the Need for Expert Knowledge: On the Example of Econometrics

Part of the Studies in Computational Intelligence book series (SCI,volume 808)

Abstract

The main purposes of econometrics are: to describe economic phenomena, and to find out how to regulate these phenomena to get the best possible results. There have been many successes in both purposes. Companies and countries actively use econometric models in making economic decisions. However, in spite of all the successes of econometrics, most economically important decisions are not based only on the econometric models – they also take into account expert opinions, and it has been shown that these opinions often drastically improve the resulting decisions. Experts – and not econometricians – are still largely in charge of the world economics. Similarly, in many other areas of human activities, ranging from sports to city planning to teaching, in spite of all the successes of mathematical models, experts are still irreplaceable. But why? In this paper, we explain this phenomenon by taking into account that many complex systems are well described by quantum equations, and in quantum physics, the best computational results are obtained when we allow the system to make kind of imprecise queries – the types that experts ask.

Keywords

  • Imprecise Queries
  • Quantum Equations
  • Fast Factorization Algorithms
  • Massive Open Online Courses
  • Deutsch-Josza Algorithm

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Baaquie, B.E.: Quantum Finance: Path Integrals and Hamiltonians for Options and Interest Rates. Camridge University Press, New York (2004)

    CrossRef  Google Scholar 

  2. Belohlavek, R., Dauben, J.W., Klir, G.J.: Fuzzy Logic and Mathematics: A Historical Perspective. Oxford University Press, New York (2017)

    MATH  Google Scholar 

  3. Buchanan, B.G., Shortliffe, E.H.: Rule Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project. Addison-Wesley, Reading (1984)

    Google Scholar 

  4. Deutsch, D., Jozsa, R.: Rapid solutions of problems by quantum computation. Proc. R. Soc. Lond. A 439, 553–558 (1992)

    MathSciNet  CrossRef  Google Scholar 

  5. Feynman, R.P.: Simulating physics with computers. Int. J. Theor. Phys. 21(6/7), 467–488 (1982)

    MathSciNet  CrossRef  Google Scholar 

  6. Feynman, R., Leighton, R., Sands, M.: The Feynman Lectures on Physics. Addison Wesley, Boston (2005)

    MATH  Google Scholar 

  7. Grover, L.K.: A fast quantum mechanical algorithm for database search. In: Proceedings of the 28th ACM Symposium on Theory of Computing, pp. 212–219 (1996)

    Google Scholar 

  8. Grover, L.K.: Quantum mechanics helps in searching for a needle in a haystack. Phys. Rev. Lett. 79(2), 325–328 (1997)

    CrossRef  Google Scholar 

  9. Grover, T.S., Wenk, S.L.: Relentless: From Good to Great to Unstoppable. Scribner, New York (2014)

    Google Scholar 

  10. Haven, E., Khrennikov, A.: Quantum Social Science. Cambridge University Press, Cambridge (2013)

    CrossRef  Google Scholar 

  11. Klir, G., Yuan, B.: Fuzzy Sets and Fuzzy Logic. Prentice Hall, Upper Saddle River (1995)

    MATH  Google Scholar 

  12. Kosheleva, O., Kreinovich, V.: How to introduce technical details of quantum computing in a theory of computation class: using the basic case of the Deutsch-Jozsa Algorithm. Int. J. Comput. Optim. 3(1), 83–91 (2016)

    Google Scholar 

  13. Kreinovich, V., Nguyen, H.T., Sriboonchitta, S.: Quantum ideas in economics beyond quantum econometrics. In: Anh, L., Dong, L., kreinovich, V., Thach, N. (eds.) Econometrics for Financial Applications, pp. 146–151. Springer, Cham (2018)

    Google Scholar 

  14. Lewis, M.: Moneyball: The Art of Winning an Unfair Game. W. W. Norton, New York (2004)

    Google Scholar 

  15. Mendel, J.M.: Uncertain Rule-Based Fuzzy Systems: Introduction and New Directions. Springer, Cham (2017)

    CrossRef  Google Scholar 

  16. Nguyen, H.T., Walker, E.A.: A First Course in Fuzzy Logic. Chapman and Hall/CRC, Boca Raton (2006)

    Google Scholar 

  17. Nielsen, M., Chuang, I.: Quantum Computation and Quantum Information. Cambridge University Press, Cambridge (2000)

    MATH  Google Scholar 

  18. Novák, V., Perfilieva, I., Močkoř, J.: Mathematical Principles of Fuzzy Logic. Kluwer, Boston (1999)

    CrossRef  Google Scholar 

  19. Schehtner, K.: Bridging the adoption gap for smart city technologies: an interview with Rob Kitchin. IEEE Pervas. Comput. 16(2), 72–75 (2017)

    CrossRef  Google Scholar 

  20. Shor, P.: Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer. In: Proceedings of the 35th Annual Symposium on Foundations of Computer Science, Santa Fe, New Mexico, 20–22 November 1994 (1994)

    Google Scholar 

  21. Shor, P.: Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer. SIAM J. Sci. Statist. Comput. 26, 1484–1509 (1997)

    MathSciNet  CrossRef  Google Scholar 

  22. Thorne, K.S., Blandford, R.D.: Modern Classical Physics: Optics, Fluids, Plasmas, Elasticity, Relativity, and Statistical Physics. Princeton University Press, Princeton (2017)

    MATH  Google Scholar 

  23. Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)

    CrossRef  Google Scholar 

Download references

Acknowledgments

This work was supported by the Center of Excellence in Econometrics, Faculty of Economics, Chiang Mai University, Thailand. We also acknowledge the partial support of the US National Science Foundation via grant HRD-1242122 (Cyber-ShARE Center of Excellence).

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Correspondence to Vladik Kreinovich .

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Sriboonchitta, S., Nguyen, H.T., Kosheleva, O., Kreinovich, V., Nguyen, T.N. (2019). Quantum Approach Explains the Need for Expert Knowledge: On the Example of Econometrics. In: Kreinovich, V., Sriboonchitta, S. (eds) Structural Changes and their Econometric Modeling. TES 2019. Studies in Computational Intelligence, vol 808. Springer, Cham. https://doi.org/10.1007/978-3-030-04263-9_15

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