Bayesian model comparison favors quantum over standard decision theory account of dynamic inconsistency.

Busemeyer, Jerome R.; Wang, Zheng; Shiffrin, Richard M.

doi:10.1037/dec0000017

Cited by 40 publications

(33 citation statements)

References 39 publications

(61 reference statements)

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“…The axioms of the classical probability theory, such as the axiom of Boolean logic and the law of total probability, do not always hold in the framework of quantum probability. On the other hand, recent work using the Bayesian model comparison method has revealed that the quantum cognition model with an interference term is more competitive with its accuracy, parsimony and robustness [15,16].…”

Section: Introductionmentioning

confidence: 99%

Exploration of Quantum Interference in Document Relevance Judgement Discrepancy

Wang

Zhang

et al. 2016

Entropy

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Quantum theory has been applied in a number of fields outside physics, e.g., cognitive science and information retrieval (IR). Recently, it has been shown that quantum theory can subsume various key IR models into a single mathematical formalism of Hilbert vector spaces. While a series of quantum-inspired IR models has been proposed, limited effort has been devoted to verify the existence of the quantum-like phenomenon in real users' information retrieval processes, from a real user study perspective. In this paper, we aim to explore and model the quantum interference in users' relevance judgement about documents, caused by the presentation order of documents. A user study in the context of IR tasks have been carried out. The existence of the quantum interference is tested by the violation of the law of total probability and the validity of the order effect. Our main findings are: (1) there is an apparent judging discrepancy across different users and document presentation orders, and empirical data have violated the law of total probability; (2) most search trials recorded in the user study show the existence of the order effect, and the incompatible decision perspectives in the quantum question (QQ) model are valid in some trials. We further explain the judgement discrepancy in more depth, in terms of four effects (comparison, unfamiliarity, attraction and repulsion) and also analyse the dynamics of document relevance judgement in terms of the evolution of the information need subspace.

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Section: Introductionmentioning

confidence: 99%

Exploration of Quantum Interference in Document Relevance Judgement Discrepancy

Wang

Zhang

et al. 2016

Entropy

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“…The Bayesian model comparison method evaluates models with respect to their accuracy, parsimony, and robustness. In the model comparison [61], the Bayes factor strongly favored the quantum model over the traditional decision models, suggesting the quantum model is more accurate and robust without being more complex than models based on classical probability theory.…”

Section: Violations Of Rational Decision Makingmentioning

confidence: 98%

“…Critics might argue that the ability of quantum models to account for all these findings relies on being more complex than their traditional counterparts. This criticism has been directly addressed by performing a rigorous quantitative comparison of quantum versus previously successful traditional, classical decision models using a Bayesian model comparison method [61]. Note that model complexity depends not only on the number of model parameters but also on its functional flexibility [62].…”

Section: Violations Of Rational Decision Makingmentioning

confidence: 99%

Quantum cognition: a new theoretical approach to psychology

Bruza

Wang

Busemeyer

2015

Trends in Cognitive Sciences

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186

134

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What type of probability theory best describes the way humans make judgments under uncertainty and decisions under conflict? Although rational models of cognition have become prominent and have achieved much success, they adhere to the laws of classical probability theory despite the fact that human reasoning does not always conform to these laws. For this reason we have seen the recent emergence of models based on an alternative probabilistic framework drawn from quantum theory. These quantum models show promise in addressing cognitive phenomena that have proven recalcitrant to modeling by means of classical probability theory. This review compares and contrasts probabilistic models based on Bayesian or classical versus quantum principles, and highlights the advantages and disadvantages of each approach.

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“…In this sense, psychological (and cognitive) models benefit from the usage of quantum probability principles because they have many advantages over classical counterparts [15]. They can represent events in vector spaces through a superposition state, which comprises the occurrence of all events at the same time.…”

Section: Introductionmentioning

confidence: 99%

Quantum Probabilistic Models Revisited: The Case of Disjunction Effects in Cognition

Moreira

Wichert

2016

Front. Phys.

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Recent work in cognitive psychology has revealed that quantum probability theory provides another method of computing probabilities without falling into the restrictions that classical probability has in regard to modeling cognitive systems and decision-making. This enables the explanation of paradoxical scenarios that are difficult, or even impossible, to explain through classical probability theory. In this work, we perform an overview of the most important quantum models in the literature that are used to make predictions under scenarios where the Sure Thing Principle is being violated (the Quantum-Like Approach, the Quantum Dynamical Model, the Quantum Prospect Theory and Quantum-Like Bayesian Networks). We evaluated these models in terms of three metrics: interference effects, parameter tuning and scalability. The first examines if the analyzed model makes use of any type of quantum interferences to explain human decision-making. The second is concerned with the assignment of values to a large number of quantum parameters. The last one consists of analyzing the ability of the models to be extended and generalized to more complex scenarios. We also studied the growth of the quantum parameters when the complexity and the levels of uncertainty of the decision scenario increase. Finally, we compared these quantum models with traditional classical models from the literature. We conclude with a discussion of the manner in which the models addressed in this paper can only deal with very small decision problems and why they do not scale well to larger, more complex decision scenarios.

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Bayesian model comparison favors quantum over standard decision theory account of dynamic inconsistency.

Cited by 40 publications

References 39 publications

Exploration of Quantum Interference in Document Relevance Judgement Discrepancy

Exploration of Quantum Interference in Document Relevance Judgement Discrepancy

Quantum cognition: a new theoretical approach to psychology

Quantum Probabilistic Models Revisited: The Case of Disjunction Effects in Cognition

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