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Quantum Machine Learning

From Classical Rationality to Contextual Reasoning: Quantum Logic as a New Frontier for Human-Centric AI in Finance

arXiv
Authors: Fabio Bagarello, Francesco Gargano, Polina Khrennikova

Year

2025

Paper ID

51748

Status

Preprint

Abstract Read

~2 min

Abstract Words

82

Citations

N/A

Abstract

We consider state of the art applications of artificial intelligence (AI) in modelling human financial expectations and explore the potential of quantum logic to drive future advancements in this field. This analysis highlights the application of machine learning techniques, including reinforcement learning and deep neural networks, in financial statement analysis, algorithmic trading, portfolio management, and robo-advisory services. We further discuss the emergence and progress of quantum machine learning (QML) and advocate for broader exploration of the advantages provided by quantum-inspired neural networks.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2025 reference point for readers tracking recent quantum research.
  • We consider state of the art applications of artificial intelligence (AI) in modelling human financial expectations and explore the potential of quantum logic to drive future...

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References & Citation Signals

[1] DOI https://doi.org/arXiv:2510.05475 [2] arXiv https://arxiv.org/abs/2510.05475 [3] Publisher https://arxiv.org/abs/2510.05475

Local Citation Graph (Related-Paper Links)

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