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Related papers: Mathematical Structure of Quantum Decision Theory

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The framework of generalized probabilistic theories is a powerful tool for studying the foundations of quantum physics. It provides the basis for a variety of recent findings that significantly improve our understanding of the rich physical…

Quantum Physics · Physics 2014-08-14 Peter Janotta , Haye Hinrichsen

The agenda of quantum algorithmic information theory, ordered `top-down,' is the quantum halting amplitude, followed by the quantum algorithmic information content, which in turn requires the theory of quantum computation. The fundamental…

Quantum Physics · Physics 2007-05-23 Karl Svozil

We present the first calibration of quantum decision theory (QDT) to a dataset of binary risky choice. We quantitatively account for the fraction of choice reversals between two repetitions of the experiment, using a probabilistic choice…

Artificial Intelligence · Computer Science 2023-03-06 T. Kovalenko , S. Vincent , V. I. Yukalov , D. Sornette

The term quantum neural computing indicates a unity in the functioning of the brain. It assumes that the neural structures perform classical processing and that the virtual particles associated with the dynamical states of the structures…

Neural and Evolutionary Computing · Computer Science 2013-03-15 Subhash Kak

On the surface, behavioural science and physics seem to be two disparate fields of research. However, a closer examination of problems solved by them reveals that they are uniquely related to one another. Exemplified by the theories of…

Physics and Society · Physics 2024-04-17 Ivan S. Maksymov

The applications of techniques from statistical (and classical) mechanics to model interesting problems in economics and finance has produced valuable results. The principal movement which has steered this research direction is known under…

General Finance · Quantitative Finance 2015-11-23 Emmanuel Haven , Sandro Sozzo

Processes undergoing quantum mechanics, exhibit quantum interference effects. In this case quantum probabilities result to be different from classical probabilities because they contain an additional main point that in fact is called the…

To make nature mathematically tractable, the scientific model of the world omits qualia--colors, sounds, tastes, sensations--leaving only what admits of numerical characterization. The "hard problem" of consciousness--the enigma of why and…

Neurons and Cognition · Quantitative Biology 2026-03-20 T. R. Le

A challenging task for word embeddings is to capture the emergent meaning or polarity of a combination of individual words. For example, existing approaches in word embeddings will assign high probabilities to the words "Penguin" and "Fly"…

Computation and Language · Computer Science 2018-05-30 Qiuchi Li , Sagar Uprety , Benyou Wang , Dawei Song

We study the following problem: Is it possible to explain the quantum interference of probabilities in the purely corpuscular model for elementary particles? We demonstrate that (by taking into account perturbation effects of measurement…

Quantum Physics · Physics 2007-05-23 Andrei Khrennikov

Quantum theory's irreducible empirical core is a probability calculus. While it presupposes the events to which (and on the basis of which) it serves to assign probabilities, and therefore cannot account for their occurrence, it has to be…

Quantum Physics · Physics 2014-11-03 Ulrich Mohrhoff

The principal goal of this paper is to pass all quantum probability formulas to the projective space associated to the complex Hilbert space of a given quantum system, providing a more complete geometrization of quantum theory. Quantum…

Quantum Physics · Physics 2025-02-18 Stephen Bruce Sontz

In quantum chemistry, the price paid by all known efficient model chemistries is either the truncation of the Hilbert space or uncontrolled approximations. Theoretical computer science suggests that these restrictions are not mere…

Chemical Physics · Physics 2017-03-15 James D. Whitfield , Peter J. Love , Alan Aspuru-Guzik

In this paper we derive the complex Hilbert space formalism of quantum theory from four simple information theoretic axioms. It is shown that quantum theory is the only non classical probabilistic theory satisfying the following axioms:…

Quantum Physics · Physics 2012-12-27 Marco Zaopo

We provide a decision-theoretic framework for dealing with uncertainty in quantum mechanics. This uncertainty is two-fold: on the one hand there may be uncertainty about the state the quantum system is in, and on the other hand, as is…

Quantum Physics · Physics 2026-05-01 Keano De Vos , Gert de Cooman , Alexander Erreygers , Jasper De Bock

An interpretation and re-formulation of modern physics which removes the presumption of the space-time continuum, and bases physical theory on a small number of rational and empirical principles. After briefly describing the philosophical…

General Physics · Physics 2014-05-13 Charles Francis

Objective probability in quantum mechanics is often thought to involve a stochastic process whereby an actual future is selected from a range of possibilities. Everett's seminal idea is that all possible definite futures on the pointer…

Quantum Physics · Physics 2017-02-09 Paul Tappenden

A network of agents is considered whose decision processes are described by the quantum decision theory previously advanced by the authors. Decision making is done by evaluating the utility of alternatives, their attractiveness, and the…

Physics and Society · Physics 2022-05-04 V. I. Yukalov , E. P. Yukalova , D. Sornette

For two decades, the formalism of quantum mechanics has been successfully used to describe human decision processes, situations of heuristic reasoning, and the contextuality of concepts and their combinations. The phenomenon of 'categorical…

Neurons and Cognition · Quantitative Biology 2023-02-27 Diederik Aerts , Jonito Aerts Arguëlles

A longstanding question in cognitive science concerns the learning mechanisms underlying compositionality in human cognition. Humans can infer the structured relationships (e.g., grammatical rules) implicit in their sensory observations…

Machine Learning · Computer Science 2021-05-20 Jacob Russin , Roland Fernandez , Hamid Palangi , Eric Rosen , Nebojsa Jojic , Paul Smolensky , Jianfeng Gao