34 found
Order:
  1.  13
    Quantum Models of Cognition and Decision.Jerome R. Busemeyer & Peter D. Bruza - 2012 - Cambridge University Press.
    Much of our understanding of human thinking is based on probabilistic models. This innovative book by Jerome R. Busemeyer and Peter D. Bruza argues that, actually, the underlying mathematical structures from quantum theory provide a much better account of human thinking than traditional models. They introduce the foundations for modelling probabilistic-dynamic systems using two aspects of quantum theory. The first, 'contextuality', is a way to understand interference effects found with inferences and decisions under conditions of uncertainty. The second, 'quantum entanglement', (...)
    No categories
    Direct download  
     
    Export citation  
     
    Bookmark   59 citations  
  2.  53
    Decision field theory: A dynamic-cognitive approach to decision making in an uncertain environment.Jerome R. Busemeyer & James T. Townsend - 1993 - Psychological Review 100 (3):432-459.
  3. Can quantum probability provide a new direction for cognitive modeling?Emmanuel M. Pothos & Jerome R. Busemeyer - 2013 - Behavioral and Brain Sciences 36 (3):255-274.
    Classical (Bayesian) probability (CP) theory has led to an influential research tradition for modeling cognitive processes. Cognitive scientists have been trained to work with CP principles for so long that it is hard even to imagine alternative ways to formalize probabilities. However, in physics, quantum probability (QP) theory has been the dominant probabilistic approach for nearly 100 years. Could QP theory provide us with any advantages in cognitive modeling as well? Note first that both CP and QP theory share the (...)
    Direct download (7 more)  
     
    Export citation  
     
    Bookmark   56 citations  
  4.  33
    A quantum theoretical explanation for probability judgment errors.Jerome R. Busemeyer, Emmanuel M. Pothos, Riccardo Franco & Jennifer S. Trueblood - 2011 - Psychological Review 118 (2):193-218.
  5.  61
    Two-stage dynamic signal detection: A theory of choice, decision time, and confidence.Timothy J. Pleskac & Jerome R. Busemeyer - 2010 - Psychological Review 117 (3):864-901.
    No categories
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   64 citations  
  6. The Potential of Using Quantum Theory to Build Models of Cognition.Zheng Wang, Jerome R. Busemeyer, Harald Atmanspacher & Emmanuel M. Pothos - 2013 - Topics in Cognitive Science 5 (4):672-688.
    Quantum cognition research applies abstract, mathematical principles of quantum theory to inquiries in cognitive science. It differs fundamentally from alternative speculations about quantum brain processes. This topic presents new developments within this research program. In the introduction to this topic, we try to answer three questions: Why apply quantum concepts to human cognition? How is quantum cognitive modeling different from traditional cognitive modeling? What cognitive processes have been modeled using a quantum account? In addition, a brief introduction to quantum probability (...)
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   37 citations  
  7. A Quantum Question Order Model Supported by Empirical Tests of an A Priori and Precise Prediction.Zheng Wang & Jerome R. Busemeyer - 2013 - Topics in Cognitive Science 5 (4):689-710.
    Question order effects are commonly observed in self-report measures of judgment and attitude. This article develops a quantum question order model (the QQ model) to account for four types of question order effects observed in literature. First, the postulates of the QQ model are presented. Second, an a priori, parameter-free, and precise prediction, called the QQ equality, is derived from these mathematical principles, and six empirical data sets are used to test the prediction. Third, a new index is derived from (...)
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   30 citations  
  8. A Quantum Probability Account of Order Effects in Inference.Jennifer S. Trueblood & Jerome R. Busemeyer - 2011 - Cognitive Science 35 (8):1518-1552.
    Order of information plays a crucial role in the process of updating beliefs across time. In fact, the presence of order effects makes a classical or Bayesian approach to inference difficult. As a result, the existing models of inference, such as the belief-adjustment model, merely provide an ad hoc explanation for these effects. We postulate a quantum inference model for order effects based on the axiomatic principles of quantum probability theory. The quantum inference model explains order effects by transforming a (...)
    Direct download  
     
    Export citation  
     
    Bookmark   25 citations  
  9. Comparison of Decision Learning Models Using the Generalization Criterion Method.Woo-Young Ahn, Jerome R. Busemeyer, Eric-Jan Wagenmakers & Julie C. Stout - 2008 - Cognitive Science 32 (8):1376-1402.
    It is a hallmark of a good model to make accurate a priori predictions to new conditions (Busemeyer & Wang, 2000). This study compared 8 decision learning models with respect to their generalizability. Participants performed 2 tasks (the Iowa Gambling Task and the Soochow Gambling Task), and each model made a priori predictions by estimating the parameters for each participant from 1 task and using those same parameters to predict on the other task. Three methods were used to evaluate the (...)
    No categories
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   20 citations  
  10.  32
    A quantum geometric model of similarity.Emmanuel M. Pothos, Jerome R. Busemeyer & Jennifer S. Trueblood - 2013 - Psychological Review 120 (3):679-696.
  11.  28
    Hilbert space multidimensional theory.Jerome R. Busemeyer & Zheng Wang - 2018 - Psychological Review 125 (4):572-591.
    No categories
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   6 citations  
  12.  29
    A Dynamic, Stochastic, Computational Model of Preference Reversal Phenomena.Joseph G. Johnson & Jerome R. Busemeyer - 2005 - Psychological Review 112 (4):841-861.
    No categories
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   14 citations  
  13. Microprocess models of decision making.Jerome R. Busemeyer & Joseph G. Johnson - 2008 - In Ron Sun (ed.), The Cambridge handbook of computational psychology. New York: Cambridge University Press. pp. 302--321.
     
    Export citation  
     
    Bookmark   6 citations  
  14.  48
    A Quantum Probability Model of Causal Reasoning.Jennifer S. Trueblood & Jerome R. Busemeyer - 2012 - Frontiers in Psychology 3.
  15.  34
    Sometimes it does hurt to ask: The constructive role of articulating impressions.Lee C. White, Emmanuel M. Pothos & Jerome R. Busemeyer - 2014 - Cognition 133 (1):48-64.
    No categories
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   5 citations  
  16.  37
    Interference effects of categorization on decision making.Zheng Wang & Jerome R. Busemeyer - 2016 - Cognition 150 (C):133-149.
    No categories
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  17.  24
    Theoretical developments in decision field theory: Comment on Tsetsos, Usher, and Chater (2010).Jared M. Hotaling, Jerome R. Busemeyer & Jiyun Li - 2010 - Psychological Review 117 (4):1294-1298.
    No categories
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   5 citations  
  18.  97
    Progress and current challenges with the quantum similarity model.Emmanuel M. Pothos, Albert Barque-Duran, James M. Yearsley, Jennifer S. Trueblood, Jerome R. Busemeyer & James A. Hampton - 2015 - Frontiers in Psychology 6.
  19.  45
    What are the appropriate axioms of rationality for reasoning under uncertainty with resource-constrained systems?Harald Atmanspacher, Irina Basieva, Jerome R. Busemeyer, Andrei Y. Khrennikov, Emmanuel M. Pothos, Richard M. Shiffrin & Zheng Wang - 2020 - Behavioral and Brain Sciences 43.
    When constrained by limited resources, how do we choose axioms of rationality? The target article relies on Bayesian reasoning that encounter serioustractabilityproblems. We propose another axiomatic foundation: quantum probability theory, which provides for less complex and more comprehensive descriptions. More generally, defining rationality in terms of axiomatic systems misses a key issue: rationality must be defined by humans facing vague information.
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  20.  54
    An improved cognitive model of the Iowa and Soochow Gambling Tasks with regard to model fitting performance and tests of parameter consistency.Junyi Dai, Rebecca Kerestes, Daniel J. Upton, Jerome R. Busemeyer & Julie C. Stout - 2015 - Frontiers in Psychology 6:126715.
    The Iowa Gambling Task (IGT) and the Soochow Gambling Task (SGT) are two experience-based risky decision-making tasks for examining decision-making deficits in clinical populations. Several cognitive models, including the expectancy-valence learning model (EVL) and the prospect valence learning model (PVL), have been developed to disentangle the motivational, cognitive, and response processes underlying the explicit choices in these tasks. The purpose of the current study was to develop an improved model that can fit empirical data better than the EVL and PVL (...)
    Direct download (6 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  21.  79
    Quantum Cognition: Key Issues and Discussion.Jerome R. Busemeyer & Zheng Wang - 2014 - Topics in Cognitive Science 6 (1):43-46.
    Quantum cognition is an emerging field that uses mathematical principles of quantum theory to help formalize and understand cognitive systems and processes. The topic on the potential of using quantum theory to build models of cognition (Volume 5, issue 4) introduces and synthesizes its new development through an introduction and six core articles. The current issue presents 14 commentaries on the core articles. Five key issues surface, some of which are interestingly controversial and debatable as expected for a new emerging (...)
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  22.  48
    Quantum principles in psychology: The debate, the evidence, and the future.Emmanuel M. Pothos & Jerome R. Busemeyer - 2013 - Behavioral and Brain Sciences 36 (3):310-327.
    The attempt to employ quantum principles for modeling cognition has enabled the introduction of several new concepts in psychology, such as the uncertainty principle, incompatibility, entanglement, and superposition. For many commentators, this is an exciting opportunity to question existing formal frameworks (notably classical probability theory) and explore what is to be gained by employing these novel conceptual tools. This is not to say that major empirical challenges are not there. For example, can we definitely prove the necessity for quantum, as (...)
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  23. Multiple-Stage Decision-Making: The Effect of Planning Horizon Length on Dynamic Consistency.Joseph G. Johnson & Jerome R. Busemeyer - 2001 - Theory and Decision 51 (2/4):217-246.
    Many decisions involve multiple stages of choices and events, and these decisions can be represented graphically as decision trees. Optimal decision strategies for decision trees are commonly determined by a backward induction analysis that demands adherence to three fundamental consistency principles: dynamic, consequential, and strategic. Previous research found that decision-makers tend to exhibit violations of dynamic and strategic consistency at rates significantly higher than choice inconsistency across various levels of potential reward. The current research extends these findings under new conditions; (...)
    Direct download (5 more)  
     
    Export citation  
     
    Bookmark   3 citations  
  24. Preferences constructed from dynamic micro-processing mechanisms.Jerome R. Busemeyer, Joseph G. Johnson & Ryan K. Jessup - 2006 - In Sarah Lichtenstein & Paul Slovic (eds.), The construction of preference. New York: Cambridge University Press. pp. 220--234.
  25.  17
    Cognitive science contributions to decision science.Jerome R. Busemeyer - 2015 - Cognition 135:43-46.
    No categories
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  26.  20
    Integrating Categorization and Decision‐Making.Rong Zheng, Jerome R. Busemeyer & Robert M. Nosofsky - 2023 - Cognitive Science 47 (1):e13235.
    Though individual categorization or decision processes have been studied separately in many previous investigations, few studies have investigated how they interact by using a two-stage task of first categorizing and then deciding. To address this issue, we investigated a categorization-decision task in two experiments. In both, participants were shown six faces varying in width, first asked to categorize the faces, and then decide a course of action for each face. Each experiment was designed to include three groups, and for each (...)
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark  
  27.  34
    Quantum probability theory as a common framework for reasoning and similarity.Jennifer S. Trueblood, Emmanuel M. Pothos & Jerome R. Busemeyer - 2014 - Frontiers in Psychology 5.
    Direct download (6 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  28.  3
    Bridging the gap between subjective probability and probability judgments: The quantum sequential sampler.Jiaqi Huang, Jerome R. Busemeyer, Zo Ebelt & Emmanuel M. Pothos - forthcoming - Psychological Review.
  29.  79
    DFT-D: a cognitive-dynamical model of dynamic decision making.Jared M. Hotaling & Jerome R. Busemeyer - 2012 - Synthese 189 (S1):67-80.
    The study of decision making has traditionally been dominated by axiomatic utility theories. More recently, an alternative approach, which focuses on the micro-mechanisms of the underlying deliberation process, has been shown to account for several "paradoxes" in human choice behavior for which simple utility-based approaches cannot. Decision field theory (DFT) is a cognitive-dynamical model of decision making and preferential choice, built on the fundamental principle that decisions are based on the accumulation of subjective evaluations of choice alternatives until a threshold (...)
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  30.  19
    Contrast Effects or Loss Aversion? Comment on Usher and McClelland (2004).Jerome R. Busemeyer, James T. Townsend, Adele Diederich & Rachel Barkan - 2005 - Psychological Review 112 (1):253-255.
    No categories
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  31.  15
    A distributional and dynamic theory of pricing and preference.Peter D. Kvam & Jerome R. Busemeyer - 2020 - Psychological Review 127 (6):1053-1078.
    No categories
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark  
  32.  16
    "Two-stage dynamic signal detection: A theory of choice, decision time, and confidence": Erratum.Timothy J. Pleskac & Jerome R. Busemeyer - 2011 - Psychological Review 118 (1):56-56.
    No categories
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark  
  33.  37
    A case for limited prescriptive normativism.Emmanuel M. Pothos & Jerome R. Busemeyer - 2011 - Behavioral and Brain Sciences 34 (5):264-265.
    Understanding cognitive processes with a formal framework necessitates some limited, internal prescriptive normativism. This is because it is not possible to endorse the psychological relevance of some axioms in a formal framework, but reject that of others. The empirical challenge then becomes identifying the remit of different formal frameworks, an objective consistent with the descriptivism Elqayam & Evans (E&E) advocate.
    Direct download (5 more)  
     
    Export citation  
     
    Bookmark  
  34.  30
    Beliefs, Actions, and Rationality in Strategical Decisions.Zheng Wang, Jerome R. Busemeyer & Brahm deBuys - 2022 - Topics in Cognitive Science 14 (3):492-507.
    A puzzling finding from research on strategic decision making concerns the effect that predictions have on future actions. Simply stating a prediction about an opponent changes the total probability (pooled over predictions) of a player taking a future action as compared to not stating any prediction. These interference effects are difficult to explain using traditional economic models, and instead these results suggest turning to a quantum cognition approach to strategic decision making.
    Direct download (4 more)  
     
    Export citation  
     
    Bookmark