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Human agents happen to judge that a conjunction of two terms is more probable than one of the terms, in contradiction with the rules of classical probabilities---this is the conjunction fallacy. One of the most discussed accounts of this…

Physics and Society · Physics 2016-06-15 Thomas Boyer-Kassem , Sébastien Duchêne , Eric Guerci

The application of principles of Quantum Mechanics in areas outside of physics has been getting increasing attention in the scientific community in an emergent discipline called Quantum Cognition. These principles have been applied to…

Quantum Physics · Physics 2017-06-20 Catarina Moreira , Andreas Wichert

This article presents a new quantum-like model for cognition explicitly based on knowledge. It is shown that this model, called QKT (quantum knowledge-based theory), is able to coherently describe some experimental results that are…

Neurons and Cognition · Quantitative Biology 2016-11-29 Riccardo Franco

The question whether indeterminism in quantum measurement outcomes is fundamental or is there a possibility of constructing a finer theory underlying quantum mechanics that allows no such indeterminism, has been debated for a long time. We…

There has been a strong recent interest in applying quantum mechanics (QM) outside physics, including in cognitive science. We analyze the applicability of QM to two basic properties in opinion polling. The first property (response…

Neurons and Cognition · Quantitative Biology 2017-02-08 Andrei Khrennikov , Irina Basieva , Ehtibar N. Dzhafarov , Jerome R. Busemeyer

Various effects in human cognition, often considered `non-classical', have been argued to be most naturally modelled by quantum-like models of decision making. We extend this approach to describe models of cognition and decision-making in…

Neurons and Cognition · Quantitative Biology 2026-04-13 Sean Tull , Masanao Ozawa

A large number of studies in cognitive science have revealed that probabilistic outcomes of certain human decisions do not agree with the axioms of classical probability theory. The field of Quantum Cognition provides an alternative…

Information Retrieval · Computer Science 2020-01-22 Sagar Uprety , Prayag Tiwari , Shahram Dehdashti , Lauren Fell , Dawei Song , Peter Bruza , Massimo Melucci

We characterize the class of quantum measurements that matches the applications of quantum theory to cognition (and decision making) - quantum-like modeling. Projective measurements describe the canonical measurements of the basic…

Artificial Intelligence · Computer Science 2025-12-15 Miho Fuyama , Andrei Khrennikov , Masanao Ozawa

Recently the mathematical formalism of quantum mechanics, especially methods of quantum probability theory, started to be widely used in a variety of applications outside of physics, e.g., cognition and psychology as well as economy and…

Neurons and Cognition · Quantitative Biology 2018-07-18 Irina Basieva , Andrei Khrennikov

The formalism of quantum theory in Hilbert space has been applied with success to the modeling and explanation of several cognitive phenomena, whereas traditional cognitive approaches were problematical. However, this 'quantum cognition…

Artificial Intelligence · Computer Science 2019-02-12 Diederik Aerts , Lyneth Beltran , Massimiliano Sassoli de Bianchi , Sandro Sozzo , Tomas Veloz

This paper demonstrates that some non-classical models of human decision-making can be run successfully as circuits on quantum computers. Since the 1960s, many observed cognitive behaviors have been shown to violate rules based on classical…

Quantum Physics · Physics 2023-03-27 Dominic Widdows , Jyoti Rani , Emmanuel Pothos

A general tension-reduction (GTR) model was recently considered to derive quantum probabilities as (universal) averages over all possible forms of non-uniform fluctuations, and explain their considerable success in describing experimental…

Artificial Intelligence · Computer Science 2017-09-07 Diederik Aerts , Massimiliano Sassoli de Bianchi

An important challenge for quantum theories of cognition and decision concerns the incorporation of memory for recently made judgments and their effects on later judgments. First, we review a general approach to measurement based on system…

Physics and Society · Physics 2025-12-15 Jerome R. Busemeyer , Masanao Ozawa , Emmanuel M. Pothos , Naotsugu Tsuchiya

A quantum probability model is introduced and used to explain human probability judgment errors including the conjunction, disjunction, inverse, and conditional fallacies, as well as unpacking effects and partitioning effects. Quantum…

General Physics · Physics 2009-09-16 Jerome R. Busemeyer , Riccardo Franco , Emmanuel M. Pothos

This paper serves as a bridge between quantum computing and analogical modeling (a general theory for predicting categories of behavior in varying contexts). Since its formulation in the early 1980s, analogical modeling has been…

Quantum Physics · Physics 2007-05-23 Royal Skousen

Physicists use quantum models to describe the behavior of physical systems. Quantum models owe their success to their interpretability, to their relation to probabilistic models (quantization of classical models) and to their high…

Machine Learning · Computer Science 2016-01-25 Cyril Stark

Relational quantum queries are sometimes capable to effectively decide between collections of mutually exclusive elementary cases without completely resolving and determining those individual instances. Thereby the set of mutually exclusive…

Quantum Physics · Physics 2019-11-05 Karl Svozil

Recently Quantum Computation has generated a lot of interest due to the discovery of a quantum algorithm which can factor large numbers in polynomial time. The usefulness of a quantum com puter is limited by the effect of errors. Simulation…

Quantum Physics · Physics 2007-05-23 Kevin M. Obenland , Alvin M. Despain

Experiments in cognitive science and decision theory show that the ways in which people combine concepts and make decisions cannot be described by classical logic and probability theory. This has serious implications for applied disciplines…

Artificial Intelligence · Computer Science 2013-01-08 Diederik Aerts , Liane Gabora , Sandro Sozzo , Tomas Veloz

There are two major approaches to building good machine learning algorithms: feeding lots of data into large models, or picking a model class with an ''inductive bias'' that suits the structure of the data. When taking the second approach…

Quantum Physics · Physics 2023-12-08 Kaitlin Gili , Guillermo Alonso , Maria Schuld
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