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Journal articles on the topic 'Quantum Decision Models'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

XIN, Xiaoyang, Chenhong XU, Hongyu CHEN, and Ying LI. "Quantum models for decision making." Advances in Psychological Science 26, no. 8 (2018): 1365. http://dx.doi.org/10.3724/sp.j.1042.2018.01365.

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Łukasik, Andrzej. "Quantum models of cognition and decision." International Journal of Parallel, Emergent and Distributed Systems 33, no. 3 (2018): 336–45. http://dx.doi.org/10.1080/17445760.2017.1410547.

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Pothos, Emmanuel M., Oliver J. Waddup, Prince Kouassi, and James M. Yearsley. "What Is Rational and Irrational in Human Decision Making." Quantum Reports 3, no. 1 (2021): 242–52. http://dx.doi.org/10.3390/quantum3010014.

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There has been a growing trend to develop cognitive models based on the mathematics of quantum theory. A common theme in the motivation of such models has been findings which apparently challenge the applicability of classical formalisms, specifically ones based on classical probability theory. Classical probability theory has had a singularly important place in cognitive theory, because of its (in general) descriptive success but, more importantly, because in decision situations with low, equivalent stakes it offers a multiply justified normative standard. Quantum cognitive models have had a

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Widdows, Dominic, Jyoti Rani, and Emmanuel Pothos. "Quantum Circuit Components for Cognitive Decision-Making." Entropy 25, no. 4 (2023): 548. http://dx.doi.org/10.3390/e25040548.

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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 probability and set theory. For example, the order in which questions are posed in a survey affects whether participants answer ‘yes’ or ‘no’, so the population that answers ‘yes’ to both questions cannot be modeled as the intersection of two fixed sets. It can, however, be modeled as a sequence of projections carried out in different orders. This and other

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5

Chinnaraju, Arunraju. "Quantum Computing in Consumer Behavior: A Theoretical Framework for Market Prediction and Decision Analytics." International Journal of Advanced Research in Science, Communication and Technology 5, no. 2 (2025): 339–71. https://doi.org/10.48175/ijarsct-23352.

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<strong>This is the author-archived version of the article titled</strong><em>“Quantum Computing in Consumer Behavior: A Theoretical Framework for Market Prediction and Decision Analytics”</em>,published in <em>International Journal of Advanced Research in Science, Communication and Technology (IJARSCT)</em>, Vol. 5, Issue 2, February 2025. The official published version is available at: https://doi.org/10.48175/IJARSCT-23352 URL: https://ijarsct.co.in/Paper23352.pdf This version has been deposited on Zenodo to enhance academic visibility and ensure indexing through scholarly datab

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Ardiansyah, Muhammad, and Vebri Sugiharto. "QUANTUM BUSINESS MODEL IN QUANTUM THEORY-BASED BUSINESS STRATEGY FOR DECISION MAKING." Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA) 9, no. 1 (2025): 2461–76. https://doi.org/10.31955/mea.v9i1.5428.

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Traditional business decision models rely on classical probability and deterministic logic, which often fail to capture uncertainty, paradoxical behaviors, and dynamic market conditions. Quantum theory offers an alternative framework, introducing quantum probability, superposition, and entanglement to improve strategic decision-making. This research adopts a qualitative approach, incorporating expert interviews and secondary data analysis to explore the feasibility of a Quantum Business Model (QBM) in real-world business applications. The study investigates quantum probability in decision-maki

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Qiang SUN. "Quantum Interference Effects in Social Decision-Making." Quantum Social Science 1, no. 1 (2025): 70–92. https://doi.org/10.6914/qss.010102.

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Quantum interference effects play a fundamental role in social decision-making, offering a novel perspective beyond classical decision theories. This study explores the theoretical foundations of quantum decision-making, emphasizing the role of quantum probability in explaining cognitive biases, preference reversals, and decision anomalies. The research presents a quantum probability-based decision model and contrasts it with classical probability models. Through theoretical modeling and experimental design, we demonstrate how quantum interference alters decision probabilities and impacts grou

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Yearsley, James M., and Emmanuel M. Pothos. "Zeno's paradox in decision-making." Proceedings of the Royal Society B: Biological Sciences 283, no. 1828 (2016): 20160291. http://dx.doi.org/10.1098/rspb.2016.0291.

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Classical probability theory has been influential in modelling decision processes, despite empirical findings that have been persistently paradoxical from classical perspectives. For such findings, some researchers have been successfully pursuing decision models based on quantum theory (QT). One unique feature of QT is the collapse postulate, which entails that measurements (or in decision-making, judgements) reset the state to be consistent with the measured outcome. If there is quantum structure in cognition, then there has to be evidence for the collapse postulate. A striking, a priori pred

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Kvam, Peter D., Timothy J. Pleskac, Shuli Yu, and Jerome R. Busemeyer. "Interference effects of choice on confidence: Quantum characteristics of evidence accumulation." Proceedings of the National Academy of Sciences 112, no. 34 (2015): 10645–50. http://dx.doi.org/10.1073/pnas.1500688112.

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Decision-making relies on a process of evidence accumulation which generates support for possible hypotheses. Models of this process derived from classical stochastic theories assume that information accumulates by moving across definite levels of evidence, carving out a single trajectory across these levels over time. In contrast, quantum decision models assume that evidence develops over time in a superposition state analogous to a wavelike pattern and that judgments and decisions are constructed by a measurement process by which a definite state of evidence is created from this indefinite s

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John Jung Park. "Decision-Making & Quantum Mechanical Models of Cognitive Processing." Journal of Cognitive Science 17, no. 2 (2016): 199–228. http://dx.doi.org/10.17791/jcs.2016.17.2.199.

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11

White, Lee C., Emmanuel M. Pothos, and Jerome R. Busemeyer. "Insights from quantum cognitive models for organizational decision making." Journal of Applied Research in Memory and Cognition 4, no. 3 (2015): 229–38. http://dx.doi.org/10.1016/j.jarmac.2014.11.002.

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Xiao, Jingmei, Mei Cai, and Yu Gao. "A VIKOR-Based Linguistic Multi-Attribute Group Decision-Making Model in a Quantum Decision Scenario." Mathematics 10, no. 13 (2022): 2236. http://dx.doi.org/10.3390/math10132236.

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Quantum decision theory has been successfully applied to multi-attribute group decision-making (MAGDM) to model decision-makers’ interference and superposition effects in recent years. Existing quantum models assume that interference effects among decision-makers are symmetric. However, asymmetric interference effects have been ignored. We propose a VIKOR-based linguistic distribution assessments (LDAs) model considering asymmetric interference effects in a quantum decision scenario. Firstly, we combine VIKOR with LDAs to obtain a compromise solution in a fuzzy multi-attribute decision scenari

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Balu, Radhakrishnan, Dale Shires, and Raju Namburu. "A quantum algorithm for uniform sampling of models of propositional logic based on quantum probability." Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 16, no. 1 (2016): 57–65. http://dx.doi.org/10.1177/1548512916648232.

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We describe a class of quantum algorithms to generate models of propositional logic with equal probability. We consider quantum stochastic flows that are the quantum analogues of classical Markov chains and establish a relation between fixed points on the two flows. We construct chains inspired by von Neumann algorithms using uniform measures as fixed points to construct the corresponding irreversible quantum stochastic flows. We formulate sampling models of propositions in the framework of adiabatic quantum computing and solve the underlying satisfiability instances. Satisfiability formulatio

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LI, CHANGKUI. "Quantum Probability Theory and Social Behavior Modeling: From Axioms to Applications." Quantum Social Science 1, no. 1 (2025): 1–69. https://doi.org/10.6914/qss.010101.

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Quantum probability theory, originally developed in the context of quantum mechanics, has increasingly been applied to social sciences to explain decision-making, cognition, and collective behavior. Unlike classical probability models, which assume pre-existing and well-defined preferences, quantum models incorporate superposition, interference, and non-commutativity to capture the contextual dependence and measurement effects observed in human decisions. This paper systematically explores the theoretical foundations of quantum probability in social sciences, discusses model construction techn

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Sophia LI. "Analysis of the Impact of Quantum Social Science on Future Urban Governance." Quantum Social Science 1, no. 1 (2025): 144–75. https://doi.org/10.6914/qss.01015.

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Quantum social science provides a novel theoretical and methodological framework for addressing the complexities of future urban governance. This study explores the applications of quantum probability, quantum measurement effects, quantum game theory, and quantum computing in optimizing decision-making, enhancing policy simulations, and improving urban resource allocation. The findings highlight that quantum approaches enable more adaptive, intelligent, and transparent governance models, overcoming the limitations of classical decision-making frameworks. However, challenges such as quantum com

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Khrennikov, Andrei. "Open Systems, Quantum Probability, and Logic for Quantum-like Modeling in Biology, Cognition, and Decision-Making." Entropy 25, no. 6 (2023): 886. http://dx.doi.org/10.3390/e25060886.

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The aim of this review is to highlight the possibility of applying the mathematical formalism and methodology of quantum theory to model behavior of complex biosystems, from genomes and proteins to animals, humans, and ecological and social systems. Such models are known as quantum-like, and they should be distinguished from genuine quantum physical modeling of biological phenomena. One of the distinguishing features of quantum-like models is their applicability to macroscopic biosystems or, to be more precise, to information processing in them. Quantum-like modeling has its basis in quantum i

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Busemeyer, Jerome R., Zheng Wang, and Ariane Lambert-Mogiliansky. "Empirical comparison of Markov and quantum models of decision making." Journal of Mathematical Psychology 53, no. 5 (2009): 423–33. http://dx.doi.org/10.1016/j.jmp.2009.03.002.

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Zhong CHEN. "Quantum Superposition and Measurement Effects in Social Interaction Experiments." Quantum Social Science 1, no. 1 (2025): 117–43. https://doi.org/10.6914/qss.010104.

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Quantum computing introduces a transformative approach to social science research by integrating quantum probability models into social interaction experiments. This study examines the effects of quantum superposition, measurement-induced state collapse, and interference on decision-making processes. Compared to classical probability models, quantum approaches offer a more accurate representation of cognitive uncertainty, preference reversals, and contextual dependencies. The research highlights the advantages of quantum measurement in survey design, behavioral analysis, and policy simulations

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Manasi, Sharma. "Quantum Reinforcement Learning for Data-Driven Decision-Making in Autonomous Systems." International Journal of Novel Research and Development 9, no. 11 (2024): b429—b442. https://doi.org/10.5281/zenodo.14263962.

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Quantum Reinforcement Learning (QRL) is a cutting-edge field combining quantum computing with reinforcement learning (RL), aiming to improve the decision-making capabilities of autonomous systems. By exploiting quantum principles like superposition and entanglement, QRL offers notable improvements over classical RL in areas such as computational speed, accuracy, and energy efficiency. This paper presents detailed empirical results, simulations, and theoretical models demonstrating the superiority of QRL over classical methods, particularly in high-complexity environments like autonomous drones

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20

Yao, Qi, Yanhui Li, and Huan Gao. "Optimizing low-carbon strategies in dual-channel supply chains: A quantum game perspective." PLOS One 20, no. 6 (2025): e0323564. https://doi.org/10.1371/journal.pone.0323564.

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The carbon emission management and resource allocation optimization of dual-channel supply chain are of great significance for promoting low-carbon economy and improving supply chain efficiency. In contrast to conventional game theory, Quantum game theory can describe the cooperation and competition of online and offline channels more flexibly through quantum entanglement, so as to overcome the limitations of traditional game theory. We study the application of quantum game theory in low-carbon economy and pricing strategies, and explore how to optimize pricing strategies and improve the low-c

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Busemeyer, Jerome, Qizi Zhang, S. N. Balakrishnan, and Zheng Wang. "Application of Quantum—Markov Open System Models to Human Cognition and Decision." Entropy 22, no. 9 (2020): 990. http://dx.doi.org/10.3390/e22090990.

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Markov processes, such as random walk models, have been successfully used by cognitive and neural scientists to model human choice behavior and decision time for over 50 years. Recently, quantum walk models have been introduced as an alternative way to model the dynamics of human choice and confidence across time. Empirical evidence points to the need for both types of processes, and open system models provide a way to incorporate them both into a single process. However, some of the constraints required by open system models present challenges for achieving this goal. The purpose of this arti

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Nida, Bhanu Raju. "From Classical to Quantum: The Future of Advanced Analytics with Quantum Computing." International Journal of Multidisciplinary Research and Growth Evaluation. 6, no. 2 (2025): 587–93. https://doi.org/10.54660/.ijmrge.2025.6.2.587-593.

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The rapid growth of complex analytics has moved from classical statistical methods to the AI-based systems using large data sets for predictive and prescriptive decision making. Although the traditional computing systems have greatly improved decision-making abilities, they have their limitations in the complex and large-scale data collection and real time processing and analysis. Quantum computing is a major step forward in the enhancement of computational capability with the help of principles such as superposition and entanglement to perform several calculations at a time. This paper explor

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Njegovanović, Ana. "Approach to Financial Decision Making within Quantum Physics and Neurosciences." International Journal of Law and Public Administration 3, no. 2 (2020): 1. http://dx.doi.org/10.11114/ijlpa.v3i2.4991.

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This paper focuses on the study of the functional relationships between the tools of neuroscience, neurofinance and psychology on the one hand, and quantum physics / quantum mechanics and neurophysiology on the other. Can physics / quantum mechanics help explain / understand human behavior through the Shrödinger cat platform (perhaps we can explain the most mysterious phenomena: human behavior - cerebral secretion?)? The concepts of quantum mechanics allow a good prediction of human decision making within Schrödinger's cat (two particles can talk to each other even at a distance of a galaxy, p

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24

Chuvakov, Aleksandr, and Rodion Boryaev. "Factoring Decision Support System Based on Optimized Quantum Algorithms QMC." Informatics and Automation 24, no. 2 (2025): 657–83. https://doi.org/10.15622/ia.24.2.11.

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The continuous growth of financial markets dictates the need for its participants to seek new approaches to financial analysis to gain competitive advantages, including through the use of new approaches in the field of computing. Quantum computing can be used as a tool for obtaining these advantages over competitors. In particular, Monte Carlo modeling, although widely used in financial risk management, requires significant computing resources due to the large number of scenarios required to obtain an accurate result. To optimize this approach, quantum amplitude estimation algorithms are used,

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Tian, Jinkai, and Wenjing Yang. "Mapping Data to Concepts: Enhancing Quantum Neural Network Transparency with Concept-Driven Quantum Neural Networks." Entropy 26, no. 11 (2024): 902. http://dx.doi.org/10.3390/e26110902.

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We introduce the concept-driven quantum neural network (CD-QNN), an innovative architecture designed to enhance the interpretability of quantum neural networks (QNNs). CD-QNN merges the representational capabilities of QNNs with the transparency of self-explanatory models by mapping input data into a human-understandable concept space and making decisions based on these concepts. The algorithmic design of CD-QNN is comprehensively analyzed, detailing the roles of the concept generator, feature extractor, and feature integrator in improving and balancing model expressivity and interpretability.

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Hancock, Thomas O., Jan Broekaert, Stephane Hess, and Charisma F. Choudhury. "Quantum choice models: A flexible new approach for understanding moral decision-making." Journal of Choice Modelling 37 (December 2020): 100235. http://dx.doi.org/10.1016/j.jocm.2020.100235.

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Maksymov, Ivan S., and Ganna Pogrebna. "Quantum-Mechanical Modelling of Asymmetric Opinion Polarisation in Social Networks." Information 15, no. 3 (2024): 170. http://dx.doi.org/10.3390/info15030170.

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We propose a quantum-mechanical model that represents a human system of beliefs as the quantised energy levels of a physical system. This model represents a novel perspective on opinion dynamics, recreating a broad range of experimental and real-world data that exhibit an asymmetry of opinion radicalisation. In particular, the model demonstrates the phenomena of pronounced conservatism versus mild liberalism when individuals are exposed to opposing views, mirroring recent findings on opinion polarisation via social media exposure. Advancing this model, we establish a robust framework that inte

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Lozada Aguilar, Miguel Ángel, Andrei Khrennikov, and Klaudia Oleschko. "From axiomatics of quantum probability to modelling geological uncertainty and management of intelligent hydrocarbon reservoirs with the theory of open quantum systems." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 376, no. 2118 (2018): 20170225. http://dx.doi.org/10.1098/rsta.2017.0225.

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As was recently shown by the authors, quantum probability theory can be used for the modelling of the process of decision-making (e.g. probabilistic risk analysis) for macroscopic geophysical structures such as hydrocarbon reservoirs. This approach can be considered as a geophysical realization of Hilbert's programme on axiomatization of statistical models in physics (the famous sixth Hilbert problem). In this conceptual paper , we continue development of this approach to decision-making under uncertainty which is generated by complexity, variability, heterogeneity, anisotropy, as well as the

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Humr, Scott, Mustafa Canan, and Mustafa Demir. "A Quantum Probability Approach to Improving Human–AI Decision Making." Entropy 27, no. 2 (2025): 152. https://doi.org/10.3390/e27020152.

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Artificial intelligence is set to incorporate additional decision space that has traditionally been the purview of humans. However, AI systems that support decision making also entail the rationalization of AI outputs by humans. Yet, incongruencies between AI and human rationalization processes may introduce uncertainties in human decision making, which require new conceptualizations to improve the predictability of these interactions. The application of quantum probability theory (QPT) to human cognition is on the ascent and warrants potential consideration to human–AI decision making to impr

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Gainutdinova, A. F. "Quantum and classical nondeterministic OBDDs." Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki 166, no. 4 (2024): 470–84. https://doi.org/10.26907/2541-7746.2024.4.470-484.

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A model of nondeterministic ordered binary decision diagrams (NOBDDs) was analyzed. A method for proving a lower bound on the complexity of quantum NOBDDs was developed. Two functions were introduced: one function has linear complexity in the quantum NOBDD but constant complexity in the classical NOBDD, while the other function demonstrates the same complexity in both quantum and classical NOBDD models. The relationships among the complexity classes specific to the OBDD model were described.

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Chang, Yu-Chung. "Quantum game perspective on green product optimal pricing under emission reduction cooperation of dual-channel supply chain." Journal of Business & Industrial Marketing 38, no. 13 (2023): 74–91. http://dx.doi.org/10.1108/jbim-02-2022-0094.

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Purpose From the quantum game perspective, this paper aims to study a green product optimal pricing problem of the dual-channel supply chain under the cooperation of the retailer and manufacturer to reduce carbon emissions. Design/methodology/approach The decentralized and centralized decision-making optimal prices and profits are obtained by establishing the classical and quantum game models. Then the classical game and quantum game are compared. Findings When the quantum entanglement is greater than 0, the selling prices of the quantum model are higher than the classical model. Through theor

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32

Tamura, Leonardo Yuji. "THE MAKING OF DECISION MAKING." Administração: Ensino e Pesquisa 17, no. 1 (2016): 177–99. http://dx.doi.org/10.13058/raep.2016.v17n1.416.

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Quantum Electronics was a Brazilian startup in the 1990's that was acquired by an American equity fund in 2012. They are currently the largest manufacturer of vehicle tracking and infotainment systems. The company was founded by three college friends, who are currently executives at the company: Camilo Santos, Pedro Barbosa and Luana Correa. Edward Hutter was sent by the equity fund to take over the company’s finances, but is having trouble making organizational decisions with his colleagues. As a consultant, I was called to help them improve their decision making process and project prioritiz

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Ganapathy, Venkatasubramanian. "Comprehensive Review Of Adversarial Quantum Attacks On AI." Edumania-An International Multidisciplinary Journal 3, no. 2 (2025): 3–32. https://doi.org/10.59231/edumania/9114.

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With the rapid advancement of artificial intelligence (AI) and quantum computing, cybersecurity threats have evolved, giving rise to adversarial quantum attacks. These attacks exploit the vulnerabilities of AI models using quantum algorithms, posing a significant risk to data security, model robustness, and decision-making systems. This paper presents a comprehensive review of adversarial quantum attacks on AI, analyzing their mechanisms, potential impacts, and countermeasures. It explores how quantum computing can enhance adversarial attacks by accelerating the generation of adversarial examp

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Athalye, Vikram, and Emmanuel Haven. "Socio-Economic Sciences: Beyond Quantum Math-like Formalisms." Quantum Reports 3, no. 4 (2021): 656–63. http://dx.doi.org/10.3390/quantum3040041.

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Since the beginning of the 21st century, a new interdisciplinary research movement has started, which aims at developing quantum math-like (or simply quantum-like) models to provide an explanation for a variety of socio-economic processes and human behaviour. By making use of mainly the probabilistic aspects of quantum theory, this research movement has led to many important results in the areas of decision-making and finance. In this article, we introduce a novel and more exhaustive approach, to analyze the socio-economic processes and activities, than the pure quantum math-like modelling app

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Hao, Yidi, Baodong Qin, and Yitian Sun. "Privacy-Preserving Decision-Tree Evaluation with Low Complexity for Communication." Sensors 23, no. 5 (2023): 2624. http://dx.doi.org/10.3390/s23052624.

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Due to the rapid development of machine-learning technology, companies can build complex models to provide prediction or classification services for customers without resources. A large number of related solutions exist to protect the privacy of models and user data. However, these efforts require costly communication and are not resistant to quantum attacks. To solve this problem, we designed a new secure integer-comparison protocol based on fully homomorphic encryption and proposed a client-server classification protocol for decision-tree evaluation based on the secure integer-comparison pro

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Marewski, Julian N., and Ulrich Hoffrage. "Processes models, environmental analyses, and cognitive architectures: Quo vadis quantum probability theory?" Behavioral and Brain Sciences 36, no. 3 (2013): 297–98. http://dx.doi.org/10.1017/s0140525x12003032.

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AbstractA lot of research in cognition and decision making suffers from a lack of formalism. The quantum probability program could help to improve this situation, but we wonder whether it would provide even more added value if its presumed focus on outcome models were complemented by process models that are, ideally, informed by ecological analyses and integrated into cognitive architectures.

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Kitzmann, Harald. "Holistic Modelling Approach for the Management of Organisations." SHS Web of Conferences 126 (2021): 06003. http://dx.doi.org/10.1051/shsconf/202112606003.

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Developments in digitalization are in actual scientific discussion with leading focus on the automatizing of tasks especially in managers´ decision making, but also cover the view on the daily managerial task-fulfilment with digitalized solutions. Challenge for the managers is hereby the design of the digitalized work in a human-task-technology system by using advanced working models, methods and solutions. This compels to rethink causal-deterministic approaches and find new solutions, which especially occur in tasks of the strategic management. The purpose of this study was twofold. The first

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Chen, Ming, Giuseppe M. Ferro, and Didier Sornette. "On the use of discrete-time quantum walks in decision theory." PLOS ONE 17, no. 8 (2022): e0273551. http://dx.doi.org/10.1371/journal.pone.0273551.

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We present a short review of discrete-time quantum walks (DTQW) as a potentially useful and rich formalism to model human decision-making. We present a pedagogical introduction of the underlying formalism and main structural properties. We suggest that DTQW are particularly suitable for combining the two strands of literature on evidence accumulator models and on the quantum formalism of cognition. Due to the additional spin degree of freedom, models based on DTQW allow for a natural modeling of model choice and confidence rating in separate bases. Levels of introspection and self-assessment d

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Plotnitsky, Arkady. "On “Decisions and Revisions Which a Minute Will Reverse”: Consciousness, The Unconscious and Mathematical Modeling of Thinking." Entropy 23, no. 8 (2021): 1026. http://dx.doi.org/10.3390/e23081026.

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This article considers a partly philosophical question: What are the ontological and epistemological reasons for using quantum-like models or theories (models and theories based on the mathematical formalism of quantum theory) vs. classical-like ones (based on the mathematics of classical physics), in considering human thinking and decision making? This question is only partly philosophical because it also concerns the scientific understanding of the phenomena considered by the theories that use mathematical models of either type, just as in physics itself, where this question also arises as a

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Li, Wen, Shuaicheng Lu, Zhiliang Ren, and Obaid Ur Rehman. "A Novel Multi-Criteria Quantum Group Decision-Making Model Considering Decision Makers’ Risk Perception Based on Type-2 Fuzzy Numbers." Symmetry 17, no. 7 (2025): 1006. https://doi.org/10.3390/sym17071006.

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In multi-criteria group decision making, decision makers are commonly regarded as independent. However, in practice, heterogeneous backgrounds and complex cognitive processes lead to mutual interference among their judgments. To address this gap, a novel multi-criteria quantum group decision-making model is proposed that explicitly incorporates opinion interference effects. First, type-2 fuzzy numbers are employed to represent evaluation information, and a specialized Euclidean distance measure for them is introduced. Second, an extended distance-based criteria importance through an inter-crit

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Mangharamani, Ruchi, and Dr Gaurav Raj. "Quantum-Driven Predictive Healthcare: Next-Gen Risk Modeling & AI-Powered Decision Support." International Journal of Research in all Subjects in Multi Languages 13, no. 3 (2025): 140–51. https://doi.org/10.63345/ijrsml.v13.i3.9.

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Quantum-Driven Predictive Healthcare represents a pioneering integration of quantum computing principles with advanced risk modeling and artificial intelligence to revolutionize medical decision support systems. This approach harnesses quantum algorithms to process vast, complex healthcare datasets, enabling rapid identification of subtle patterns and correlations that traditional computing systems may overlook. By incorporating quantum-enhanced risk modeling, clinicians can benefit from more precise predictions of disease progression and patient outcomes, ultimately facilitating early interve

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Ranga, Deepak, Sunil Prajapat, Zahid Akhtar, Pankaj Kumar, and Athanasios V. Vasilakos. "Hybrid Quantum–Classical Neural Networks for Efficient MNIST Binary Image Classification." Mathematics 12, no. 23 (2024): 3684. http://dx.doi.org/10.3390/math12233684.

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Image classification is a fundamental task in deep learning, and recent advances in quantum computing have generated significant interest in quantum neural networks. Traditionally, Convolutional Neural Networks (CNNs) are employed to extract image features, while Multilayer Perceptrons (MLPs) handle decision making. However, parameterized quantum circuits offer the potential to capture complex image features and define sophisticated decision boundaries. In this paper, we present a novel Hybrid Quantum–Classical Neural Network (H-QNN) for image classification, and demonstrate its effectiveness

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RAY, ASOK, SHASHI PHOHA, and SOUMIK SARKAR. "BEHAVIOR PREDICTION FOR DECISION AND CONTROL IN COGNITIVE AUTONOMOUS SYSTEMS." New Mathematics and Natural Computation 09, no. 03 (2013): 263–71. http://dx.doi.org/10.1142/s1793005713400061.

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This paper presents an innovative concept of behavior prediction for decision and control in cognitive autonomous systems. The objective is to coordinate human–machine collaboration such that human operators can assess and enable autonomous systems to utilize their experiential and unmodeled domain knowledge and perception for mission execution. The concept of quantum probability is proposed to construct a unified mathematical framework for interfacing between models of human cognition and machine intelligence.

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Dehdashti, Shahram, Lauren Fell, Abdul Karim Obeid, Catarina Moreira, and Peter Bruza. "Bistable probabilities: a unified framework for studying rationality and irrationality in classical and quantum games." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 476, no. 2237 (2020): 20190839. http://dx.doi.org/10.1098/rspa.2019.0839.

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This article presents a unified probabilistic framework that allows both rational and irrational decision-making to be theoretically investigated and simulated in classical and quantum games. Rational choice theory is a basic component of game-theoretic models, which assumes that a decision-maker chooses the best action according to their preferences. In this article, we define irrationality as a deviation from a rational choice. Bistable probabilities are proposed as a principled and straightforward means for modelling (ir)rational decision-making in games. Bistable variants of classical and

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Basieva, Irina, Vijitashwa Pandey, and Polina Khrennikova. "More Causes Less Effect: Destructive Interference in Decision Making." Entropy 24, no. 5 (2022): 725. http://dx.doi.org/10.3390/e24050725.

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We present a new experiment demonstrating destructive interference in customers’ estimates of conditional probabilities of product failure. We take the perspective of a manufacturer of consumer products and consider two situations of cause and effect. Whereas, individually, the effect of the causes is similar, it is observed that when combined, the two causes produce the opposite effect. Such negative interference of two or more product features may be exploited for better modeling of the cognitive processes taking place in customers’ minds. Doing so can enhance the likelihood that a manufactu

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Sarris, C. M., and A. N. Proto. "Quantum models for decision making and opinion dynamics the role of the Lie algebras." Quality & Quantity 48, no. 4 (2013): 1945–56. http://dx.doi.org/10.1007/s11135-013-9860-2.

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Myridis, Nikolaos E. "Quantum models of cognition and decision, by Jerome R. Busemeyer and Peter D. Bruza." Contemporary Physics 58, no. 1 (2016): 109. http://dx.doi.org/10.1080/00107514.2016.1251974.

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Surov, Ilya A. "Probabilistic prediction of “irrational” decisions from semantic composition of contexts." Journal Of Applied Informatics 19, no. 1 (2024): 125–43. http://dx.doi.org/10.37791/2687-0649-2024-19-1-125-143.

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Difficulties in prognosis of human behavior are due to the complexity of our cognition, routinely breaking the boundaries of classical rationality. The paper solves this problem for the simplest kind of such “irrational” behavior in which a single binary decision is made in three related contexts. Subjective meanings of these contexts relative to the basis decision alternative are represented by three qubit states, borrowed from quantum theory. These states are bound together by linear superpositions, which encode semantic composition of the contexts in the subject’s mind. The resulting theory

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Maksymov, Ivan S., and Ganna Pogrebna. "The Physics of Preference: Unravelling Imprecision of Human Preferences through Magnetisation Dynamics." Information 15, no. 7 (2024): 413. http://dx.doi.org/10.3390/info15070413.

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Paradoxical decision-making behaviours such as preference reversal often arise from imprecise or noisy human preferences. Harnessing the physical principle of magnetisation reversal in ferromagnetic nanostructures, we developed a model that closely reflects human decision-making dynamics. Tested against a spectrum of psychological data, our model adeptly captures the complexities inherent in individual choices. This blend of physics and psychology paves the way for fresh perspectives on understanding the imprecision of human decision-making processes, extending the reach of the current classic

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Balicka, Honorata, and Jerzy Balicki. "QUANTUM ARTIFICIAL INTELLIGENCE IN MANAGEMENT OF SELECTED BUSINESS PROCESSES." Scientific Papers of Silesian University of Technology Organization and Management Series 2024, no. 208 (2024): 9–26. https://doi.org/10.29119/1641-3466.2024.208.1.

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Purpose: The aim of the article is to present potential applications of Quantum Artificial Intelligence (QAI) in enhancing Business Process Management (BPM), with a particular focus on predictive analytics. Design/methodology/approach: The primary research methods include a critical analysis of the literature. Deep neural network testing was also conducted to identify efficient predictors and detectors for BPM systems. In addition, intensive computational experiments were carried out to analyze the quality of solutions defined by the proposed quantum-inspired algorithms. Findings: The results

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