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International Symposium on Quantum Interaction

QI 2018: Quantum Interaction pp 79–90Cite as

Balanced Quantum-Like Model for Decision Making

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11690))

Abstract

Clues from psychology indicate that human cognition is not only based on classical probability theory as explained by Kolmogorov’s axioms but additionally on quantum probability. We explore the relation between the law of total probability and its violation resulting in the law of total quantum probability. The violation results from an additional interference that influences the classical probabilities. Outgoing from this exploration we introduce a balanced Bayesian quantum-like model that is based on probability waves. The law of maximum uncertainty indicates how to choose a possible phase value of the wave resulting in a meaningful probability value.

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Acknowledgment

This work was supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with reference UID/CEC/50021/2013. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, INESC-ID and Instituto Superior Técnico, Universidade de Lisboa, Porto Salvo, Portugal

    Andreas Wichert & Catarina Moreira

  2. School of Business, University of Leicester, University Road, Leicester, LE1 7RH, UK

    Andreas Wichert & Catarina Moreira

Authors
  1. Andreas Wichert
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  2. Catarina Moreira
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Corresponding author

Correspondence to Andreas Wichert .

Editor information

Editors and Affiliations

  1. University of Oxford, Oxford, UK

    Bob Coecke

  2. Paris School of Economics, Paris, France

    Ariane Lambert-Mogiliansky

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Wichert, A., Moreira, C. (2019). Balanced Quantum-Like Model for Decision Making. In: Coecke, B., Lambert-Mogiliansky, A. (eds) Quantum Interaction. QI 2018. Lecture Notes in Computer Science(), vol 11690. Springer, Cham. https://doi.org/10.1007/978-3-030-35895-2_6

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  • DOI: https://doi.org/10.1007/978-3-030-35895-2_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-35894-5

  • Online ISBN: 978-3-030-35895-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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