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Classical Optical Modelling of Social Sciences in a Bohr–Kantian Framework

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Credible Asset Allocation, Optimal Transport Methods, and Related Topics (TES 2022)

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 429))

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Abstract

There is a recent surge of interest in proposing quantum-like models in cognition and social sciences at large. In the current paper we attempt to contribute to that growing body of literature. We distinguish our framework from other notable works like Qbism and CBD (contextuality by default) by grounding it in the larger Bohr–Kantian philosophical and conceptual paradigm. Since our modelling techniques are motivated by the classical optical model (COM), there is a simpler geometric interpretation, with tools like Poincaré sphere representation of cognitive states and a novel Pancharatnam–Berry phase, which helps visualizing deviations from classical measure theoretic predictions of decision making.

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Author information

Authors and Affiliations

  1. Center for Complexity Economics, Applied Spirituality and Public Policy (CEASP), O P Jindal Global University, Sonipat, Haryana, 131001, India

    Sudip Patra

  2. Tagore Centre for Natural Sciences and Philosophy, Rabindra Tirtha, New Town, Kolkata, 700156, India

    Partha Ghose

Authors
  1. Sudip Patra
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  2. Partha Ghose
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Correspondence to Sudip Patra .

Editor information

Editors and Affiliations

  1. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Songsak Sriboonchitta

  2. Department of Computer Science, University of Texas, El Paso, TX, USA

    Vladik Kreinovich

  3. Faculty of Economics, Center of Excellence in Econometrics, Chiang Mai University, Chiang Mai, Thailand

    Woraphon Yamaka

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Patra, S., Ghose, P. (2022). Classical Optical Modelling of Social Sciences in a Bohr–Kantian Framework. In: Sriboonchitta, S., Kreinovich, V., Yamaka, W. (eds) Credible Asset Allocation, Optimal Transport Methods, and Related Topics. TES 2022. Studies in Systems, Decision and Control, vol 429. Springer, Cham. https://doi.org/10.1007/978-3-030-97273-8_16

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