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Quantum Propensity in Economics.

David Orrell1, Monireh Houshmand2

  • 1Systems Forecasting, Toronto, ON, Canada.

Frontiers in Artificial Intelligence
|January 31, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a quantum computing-inspired economic framework, moving beyond traditional models. It uses quantum principles to explain economic behavior, offering a probabilistic and dynamic alternative.

Keywords:
quantum artificial intelligencequantum cognitionquantum computingquantum decision theoryquantum economicsquantum financequantum probability

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Area of Science:

  • Economics
  • Quantum Computing
  • Mathematical Modeling

Background:

  • Traditional neoclassical economics, based on rational utility-maximizers, faces challenges post-2007/8 financial crisis.
  • Existing models struggle to fully capture complex human decision-making and market dynamics.

Purpose of the Study:

  • To develop a consistent quantum mathematical framework for economics.
  • To propose a quantum-inspired approach to economic modeling.
  • To address limitations of traditional economic theories.

Main Methods:

  • Utilizing quantum computing principles to model economic decision-making.
  • Replacing utility functions with probabilistic propensity functions.
  • Employing quantum circuits to generate propensity functions and model cognitive phenomena.

Main Results:

  • Demonstrated modeling of cognitive phenomena like preference reversal and disjunction effect using quantum circuits.
  • Showcased the quantization of general propensity functions via entropic force.
  • Integrated quantum effects like interference and entanglement into economic decision-making models.

Conclusions:

  • The quantum approach offers a probabilistic and dynamic framework for economics.
  • This new framework can model complex human behaviors and market dynamics.
  • Potential applications include quantum artificial intelligence in economics and finance.