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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

An approach is presented treating decision theory as a probabilistic theory based on quantum techniques. Accurate definitions are given and thorough analysis is accomplished for the quantum probabilities describing the choice between…

Artificial Intelligence · Computer Science 2022-06-06 V. I. Yukalov

The willingness to trust predictions formulated by automatic algorithms is key in a vast number of domains. However, a vast number of deep architectures are only able to formulate predictions without an associated uncertainty. In this…

Image and Video Processing · Electrical Eng. & Systems 2022-09-28 Matteo Ferrante , Tommaso Boccato , Nicola Toschi

Quantum theory makes the most accurate empirical predictions and yet it lacks simple, comprehensible physical principles from which the theory can be uniquely derived. A broad class of probabilistic theories exist which all share some…

Quantum Physics · Physics 2012-04-17 Borivoje Dakic , Caslav Brukner

Quantum Language Models (QLMs) in which words are modelled as quantum superposition of sememes have demonstrated a high level of model transparency and good post-hoc interpretability. Nevertheless, in the current literature word sequences…

Computation and Language · Computer Science 2021-12-21 Yiwei Chen , Yu Pan , Daoyi Dong

Human motion prediction is an important and challenging topic that has promising prospects in efficient and safe human-robot-interaction systems. Currently, the majority of the human motion prediction algorithms are based on deterministic…

Robotics · Computer Science 2021-07-15 Jie Xu , Xingyu Chen , Xuguang Lan , Nanning Zheng

Recently developed quantum algorithms suggest that quantum computers can solve certain problems and perform certain tasks more efficiently than conventional computers. Among other reasons, this is due to the possibility of creating…

Quantum Physics · Physics 2007-05-23 Rolando D. Somma

This paper introduces the Quantified Boolean Bayesian Network (QBBN), which provides a unified view of logical and probabilistic reasoning. The QBBN is meant to address a central problem with the Large Language Model (LLM), which has become…

Artificial Intelligence · Computer Science 2024-02-12 Gregory Coppola

This paper proposes a new general approach based on Bayesian networks to model the human behaviour. This approach represents human behaviour with probabilistic cause-effect relations based on knowledge, but also with conditional…

Artificial Intelligence · Computer Science 2016-05-20 Khadija Tijani , Stephane Ploix , Benjamin Haas , Julie Dugdale , Quoc Dung Ngo

A general approach describing quantum decision procedures is developed. The approach can be applied to quantum information processing, quantum computing, creation of artificial quantum intelligence, as well as to analyzing decision…

Quantum Physics · Physics 2015-05-14 V. I. Yukalov , D. Sornette

Quantum Decision Theory, advanced earlier by the authors, and illustrated for lotteries with gains, is generalized to the games containing lotteries with gains as well as losses. The mathematical structure of the approach is based on the…

Physics and Society · Physics 2018-02-20 V. I. Yukalov , D. Sornette

Human decision-making underlies all economic behavior. For the past four decades, human decision-making under uncertainty has continued to be explained by theoretical models based on prospect theory, a framework that was awarded the Nobel…

Machine Learning · Computer Science 2019-06-21 David D. Bourgin , Joshua C. Peterson , Daniel Reichman , Thomas L. Griffiths , Stuart J. Russell

Interacting systems of events may exhibit cascading behavior where events tend to be temporally clustered. While the cascades themselves may be obvious from the data, it is important to understand which states of the system trigger them.…

Machine Learning · Statistics 2023-11-02 Alessandro Bregoli , Karin Rathsman , Marco Scutari , Fabio Stella , Søren Wengel Mogensen

When agents devise plans for execution in the real world, they face two important forms of uncertainty: they can never have complete knowledge about the state of the world, and they do not have complete control, as the effects of their…

Artificial Intelligence · Computer Science 2013-02-28 Ron Davidson , Michael R. Fehling

We define predictive states and predictive complexity for quantum systems composed of distinct subsystems. This complexity is a generalization of entanglement entropy. It is inspired by the statistical or forecasting complexity of…

Quantum Physics · Physics 2024-10-22 Curtis T. Asplund , Elisa Panciu

Binding energy is a fundamental thermodynamic property that governs molecular interactions, playing a crucial role in fields such as healthcare and the natural sciences. It is particularly relevant in drug development, vaccine design, and…

Quantum Physics · Physics 2025-08-06 Erico Souza Teixeira , Lucas Barros Fernandes , Yara Rodrigues Inácio

Categorization is a significant task in decision-making, which is a key part of human behavior. An interference effect is caused by categorization in some cases, which breaks the total probability principle. A negation quantum model (NQ…

Artificial Intelligence · Computer Science 2021-04-20 Qinyuan Wu , Yong Deng

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

Many studies have shown that there are regularities in the way human beings make decisions. However, our ability to obtain models that capture such regularities and can accurately predict unobserved decisions is still limited. We tackle…

General Finance · Quantitative Finance 2021-03-11 Gael Poux-Medard , Sergio Cobo-Lopez , Jordi Duch , Roger Guimera , Marta Sales-Pardo

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