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Quantum mechanics may be formulated as Sensible Quantum Mechanics (SQM) so that it contains nothing probabilistic, except, in a certain frequency sense, conscious perceptions. Sets of these perceptions can be deterministically realized with…

Quantum Physics · Physics 2008-02-03 Don N. Page

Conceptual problems in quantum mechanics result from the specific quantum concept of reality and require, for their solution, including the observer's consciousness into quantum theory of measurements. Most naturally this is achieved in the…

General Physics · Physics 2009-11-13 Michael B. Mensky

Quantum cognition in decision-making is a recent and rapidely growing field. In this paper we develop an expected utility theory in a context of non-classical (quantum) uncertainty. We replace the classical state space with a Hilbert space…

Physics and Society · Physics 2017-08-29 Vladimir V. Danilov , Ariane Lambert-Mogiliansky , Vassily Vergopoulos

We present a general theory of quantum information processing devices, that can be applied to human decision makers, to atomic multimode registers, or to molecular high-spin registers. Our quantum decision theory is a generalization of the…

Quantum Physics · Physics 2009-11-13 V. I. Yukalov , D. Sornette

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

A model for decision making that generalizes Expected Utility Maximization is presented. This model, Expected Qualitative Utility Maximization, encompasses the Maximin criterion. It relaxes both the Independence and the Continuity…

Computer Science and Game Theory · Computer Science 2007-05-23 Daniel Lehmann

Quantum theory, originally proposed as a physical theory to describe the motions of microscopic particles, has been applied to various non-physics domains involving human cognition and decision-making that are inherently uncertain and…

Computation and Language · Computer Science 2023-06-07 Yaochen Liu , Qiuchi Li , Benyou Wang , Yazhou Zhang , Dawei Song

We consider a decision maker who is unaware of objects to be sampled and thus cannot form beliefs about the occurrence of particular objects. Ex ante she can form beliefs about the occurrence of novelty and the frequencies of yet to be…

Theoretical Economics · Economics 2025-02-21 Burkhard C. Schipper

Trust is a crucial factor affecting the adoption of machine learning (ML) models. Qualitative studies have revealed that end-users, particularly in the medical domain, need models that can express their uncertainty in decision-making…

Machine Learning · Computer Science 2023-04-21 Andrew Houston , Georgina Cosma

We define a formal framework for reasoning about linear-time properties of quantum systems in which quantum automata are employed in the modeling of systems and certain closed subspaces of state (Hilbert) spaces are used as the atomic…

Quantum Physics · Physics 2011-01-04 Mingsheng Ying , Yangjia Li , Nengkun Yu , Yuan Feng

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 investigate the applicability of the formalism of quantum mechanics to everyday life. It seems to be directly relevant for situations in which the very act of coming to a conclusion or decision on one issue affects one's confidence about…

Artificial Intelligence · Computer Science 2018-11-13 Steven Gratton

We present an experimental illustration on the quantum sensitivity of decision making machinery. In the decision making process, we consider the role of available information, say hint, whether it influences the optimal choices. To the end,…

Quantum Physics · Physics 2019-05-15 Joong-Sung Lee , Jeongho Bang , Jinhyoung Lee , Kwang-Geol Lee

Quantitative practice across statistics, engineering, and machine learning has been transformed by the automation of inference. Predictions are produced, validated, and deployed at scale and speed that human-mediated reasoning could not…

Methodology · Statistics 2026-05-25 William Fauriat

Model selection is a necessary step in unsupervised machine learning. Despite numerous criteria and metrics, model selection remains subjective. A high degree of subjectivity may lead to questions about repeatability and reproducibility of…

Machine Learning · Computer Science 2024-01-08 Wanyi Chen , Mary L. Cummings

Einstein's article on the EPR paradox is the most cited of his works, but not many know that it was not fully representative of the way he thought about the incompleteness of the quantum formalism. Indeed, his main worry was not…

One of the most complex systems is the human brain whose formalized functioning is characterized by decision theory. We present a "Quantum Decision Theory" of decision making, based on the mathematical theory of separable Hilbert spaces.…

Artificial Intelligence · Computer Science 2010-10-29 V. I. Yukalov , D. Sornette

We present the fundamentals of the quantum theoretical approach we have developed in the last decade to model cognitive phenomena that resisted modeling by means of classical logical and probabilistic structures, like Boolean, Kolmogorovian…

Neurons and Cognition · Quantitative Biology 2023-02-27 Diederik Aerts , Massimiliano Sassoli de Bianchi , Sandro Sozzo , Tomas Veloz

In the present article we use the quantum formalism to describe the process of choice under rational ignorance. We consider as a basic task a question or an issue where the only answers are 0 and 1. We show that under rational ignorance the…

General Physics · Physics 2007-05-23 Riccardo Franco

Automated decision systems are increasingly used for consequential decision making -- for a variety of reasons. These systems often rely on sophisticated yet opaque models, which do not (or hardly) allow for understanding how or why a given…

Artificial Intelligence · Computer Science 2021-03-09 Jakob Schoeffer , Yvette Machowski , Niklas Kuehl