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Type Indeterminacy: A Model of the KT(Kahneman-Tversky)-man

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  • Ariane Lambert Mogiliansky
  • Shmuel Zamir
  • Herve Zwirn

Abstract

In this note we propose to use the mathematical formalism of Quantum Mechanics to capture the idea that agents’ preferences, in addition to being typically uncertain, can also be indeterminate. They are determined (realized, and not merely revealed) only when the action takes place. An agent is described by a state which is a superposition of potential types (or preferences or behaviors). This superposed state is projected (or ”collapses”) onto one of the possible behaviors at the time of the interaction. In addition to the main goal of modelling uncertainty of preferences which is not due to lack of information, this formalism, seems to be adequate to describe widely observed phenomena like framing and instances of noncommutativity in patterns of behavior. We propose two experiments to test the theory.

Suggested Citation

  • Ariane Lambert Mogiliansky & Shmuel Zamir & Herve Zwirn, 2003. "Type Indeterminacy: A Model of the KT(Kahneman-Tversky)-man," Discussion Paper Series dp343, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    • Handle: RePEc:huj:dispap:dp343
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    Cited by:

    1. Dino Borie, 2013. "Expected utility theory with non-commutative probability theory," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 295-315, October.
    2. Khrennikov, Andrei, 2015. "Quantum version of Aumann’s approach to common knowledge: Sufficient conditions of impossibility to agree on disagree," Journal of Mathematical Economics, Elsevier, vol. 60(C), pages 89-104.
    3. Ariane Lambert-Mogiliansky & Jerome Busemeyer, 2012. "Quantum Type Indeterminacy in Dynamic Decision-Making: Self-Control through Identity Management," Games, MDPI, vol. 3(2), pages 1-22, May.
    4. Zabaleta, O.G. & Arizmendi, C.M., 2010. "Quantum dating market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2858-2863.
    5. V. I. Yukalov & D. Sornette, 2012. "Quantum decision making by social agents," Papers 1202.4918, arXiv.org, revised Oct 2015.
    6. Godfrey Cadogan, 2012. "Representation theory for risk on markowitz-tversky-kahneman topology," Economics Bulletin, AccessEcon, vol. 32(4), pages 1-34.
    7. Ariane Lambert-Mogiliansky & François Dubois, 2015. "Transparency in Public Life. A Quantum Cognition Perspective," PSE Working Papers halshs-01064980, HAL.
    8. Ismaël Rafaï & Sébastien Duchêne & Eric Guerci & Irina Basieva & Andrei Khrennikov, 2022. "The triple-store experiment: a first simultaneous test of classical and quantum probabilities in choice over menus," Theory and Decision, Springer, vol. 92(2), pages 387-406, March.
    9. Thomas Boyer-Kassem & Sébastien Duchêne & Eric Guerci, 2016. "Quantum-like models cannot account for the conjunction fallacy," Theory and Decision, Springer, vol. 81(4), pages 479-510, November.
    10. Jerome R. Busemeyer & Jörg Rieskamp, 2014. "Psychological research and theories on preferential choice," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 3, pages 49-72, Edward Elgar Publishing.
    11. Siegfried K. Berninghaus & Lora R. Todorova & Bodo Vogt, 2012. "How Sensitive is Strategy Selection in Coordination Games?," FEMM Working Papers 120020, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    12. Jerry Busemeyer & Ariane Lambert-Mogiliansky, 2009. "TI-games I: An exploration of Type Indeterminacy in strategic decision-making," Working Papers halshs-00566780, HAL.
    13. Loretta Mastroeni & Maurizio Naldi & Pierluigi Vellucci, 2023. "Personal Finance Decisions with Untruthful Advisors: An Agent-Based Model," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1477-1522, April.
    14. Aerts, Diederik & Broekaert, Jan & Czachor, Marek & Kuna, Maciej & Sinervo, Barry & Sozzo, Sandro, 2014. "Quantum structure in competing lizard communities," Ecological Modelling, Elsevier, vol. 281(C), pages 38-51.
    15. Vladimir Ivanovitch Danilov & Ariane Lambert-Mogiliansky, 2005. "Non-classical measurement theory: a framework forbehavioral sciences," Working Papers halshs-00590714, HAL.
    16. Adam Brandenburger, 2007. "A Connection Between Correlation in Game Theory and Quantum Mechanics," Levine's Working Paper Archive 122247000000001725, David K. Levine.
    17. John Duffy & Ted Loch-Temzelides, 2021. "A double-slit experiment with human subjects," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-7, February.
    18. Emmanuel Haven, 2008. "Private Information and the ‘Information Function’: A Survey of Possible Uses," Theory and Decision, Springer, vol. 64(2), pages 193-228, March.
    19. Boyer-Kassem, Thomas & Duchêne, Sébastien & Guerci, Eric, 2016. "Testing quantum-like models of judgment for question order effect," Mathematical Social Sciences, Elsevier, vol. 80(C), pages 33-46.
    20. V. Danilov & A. Lambert-Mogiliansky, 2010. "Expected utility theory under non-classical uncertainty," Theory and Decision, Springer, vol. 68(1), pages 25-47, February.
    21. Vladimir Danilov, 2009. "Modelling of Non-Commuting Measurements," Journal of the New Economic Association, New Economic Association, issue 1-2, pages 10-36.
    22. Adam Brandenburger, 2008. "The Relationship Between Classical and Quantum Correlation in Games," Levine's Working Paper Archive 122247000000002312, David K. Levine.
    23. Lora R. Todorova, 2012. "Quantum Risk Preferences in a Laboratory Experiment," FEMM Working Papers 120025, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    24. Jerry Busemeyer & Ariane Lambert-Mogiliansky, 2009. "TI-games I: An exploration of Type Indeterminacy in strategic decision-making," PSE Working Papers halshs-00566780, HAL.
    25. Haven, Emmanuel & Sozzo, Sandro, 2016. "A generalized probability framework to model economic agents' decisions under uncertainty," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 297-303.

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    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology

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