31 found
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  1. 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 (...)
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  2.  32
    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.
  3. 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 (...)
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  4. A Quantum Probability Perspective on Borderline Vagueness.Reinhard Blutner, Emmanuel M. Pothos & Peter Bruza - 2013 - Topics in Cognitive Science 5 (4):711-736.
    The term “vagueness” describes a property of natural concepts, which normally have fuzzy boundaries, admit borderline cases, and are susceptible to Zeno's sorites paradox. We will discuss the psychology of vagueness, especially experiments investigating the judgment of borderline cases and contradictions. In the theoretical part, we will propose a probabilistic model that describes the quantitative characteristics of the experimental finding and extends Alxatib's and Pelletier's () theoretical analysis. The model is based on a Hopfield network for predicting truth values. Powerful (...)
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  5.  63
    A simplicity principle in unsupervised human categorization.Emmanuel M. Pothos & Nick Chater - 2002 - Cognitive Science 26 (3):303-343.
    We address the problem of predicting how people will spontaneously divide into groups a set of novel items. This is a process akin to perceptual organization. We therefore employ the simplicity principle from perceptual organization to propose a simplicity model of unconstrained spontaneous grouping. The simplicity model predicts that people would prefer the categories for a set of novel items that provide the simplest encoding of these items. Classification predictions are derived from the model without information either about the number (...)
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  6.  32
    A quantum geometric model of similarity.Emmanuel M. Pothos, Jerome R. Busemeyer & Jennifer S. Trueblood - 2013 - Psychological Review 120 (3):679-696.
  7. The rules versus similarity distinction.Emmanuel M. Pothos - 2005 - Behavioral and Brain Sciences 28 (1):1-14.
    The distinction between rules and similarity is central to our understanding of much of cognitive psychology. Two aspects of existing research have motivated the present work. First, in different cognitive psychology areas we typically see different conceptions of rules and similarity; for example, rules in language appear to be of a different kind compared to rules in categorization. Second, rules processes are typically modeled as separate from similarity ones; for example, in a learning experiment, rules and similarity influences would be (...)
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  8.  24
    One or two dimensions in spontaneous classification: A simplicity approach.Emmanuel M. Pothos & James Close - 2008 - Cognition 107 (2):581-602.
  9.  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.
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  10.  53
    Exemplar similarity and rule application.Ulrike Hahn, Mercè Prat-Sala, Emmanuel M. Pothos & Duncan P. Brumby - 2010 - Cognition 114 (1):1-18.
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  11.  95
    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.
  12.  46
    Measuring category intuitiveness in unconstrained categorization tasks.Emmanuel M. Pothos, Amotz Perlman, Todd M. Bailey, Ken Kurtz, Darren J. Edwards, Peter Hines & John V. McDonnell - 2011 - Cognition 121 (1):83-100.
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  13.  44
    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.
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  14.  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 (...)
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  15.  87
    Patterns and evolution of moral behaviour: moral dynamics in everyday life.Albert Barque-Duran, Emmanuel M. Pothos, James M. Yearsley & James A. Hampton - 2016 - Thinking and Reasoning 22 (1):31-56.
    Recent research on moral dynamics shows that an individual's ethical mind-set moderates the impact of an initial ethical or unethical act on the likelihood of behaving ethically on a subsequent occasion. More specifically, an outcome-based mind-set facilitates Moral Balancing, whereas a rule-based mind-set facilitates Moral Consistency. The objective was to look at the evolution of moral choice across a series of scenarios, that is, to explore if these moral patterns are maintained over time. The results of three studies showed that (...)
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  16.  26
    A Quantum Geometric Framework for Modeling Color Similarity Judgments.Gunnar P. Epping, Elizabeth L. Fisher, Ariel M. Zeleznikow-Johnston, Emmanuel M. Pothos & Naotsugu Tsuchiya - 2023 - Cognitive Science 47 (1):e13231.
    Since Tversky argued that similarity judgments violate the three metric axioms, asymmetrical similarity judgments have been particularly challenging for standard, geometric models of similarity, such as multidimensional scaling. According to Tversky, asymmetrical similarity judgments are driven by differences in salience or extent of knowledge. However, the notion of salience has been difficult to operationalize, especially for perceptual stimuli for which there are no apparent differences in extent of knowledge. To investigate similarity judgments between perceptual stimuli, across three experiments, we collected (...)
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  17.  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.
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  18.  37
    Role of prior knowledge in implicit and explicit learning of artificial grammars.Eleni Ziori, Emmanuel M. Pothos & Zoltán Dienes - 2014 - Consciousness and Cognition 28:1-16.
  19.  24
    Linguistic structure and short term memory.Emmanuel M. Pothos & Patrick Juola - 2001 - Behavioral and Brain Sciences 24 (1):138-139.
    We provide additional support for Cowan's claim that short term memory (STM) involves a range of 3–5 tokens, on the basis of language correlational analyses. If language is at least partly learned, linguistic dependency structure should reflect properties of the cognitive components mediating learning; one such component is STM. In this view, the range over which statistical regularity extends in ordinary text would be suggestive of STM span. Our analyses of eight languages are consistent with STM span being about four (...)
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  20.  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.
  21.  35
    Rethinking Rationality.Emmanuel M. Pothos & Timothy J. Pleskac - 2022 - Topics in Cognitive Science 14 (3):451-466.
    Topics in Cognitive Science, Volume 14, Issue 3, Page 451-466, July 2022.
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  22.  14
    Rules and similarity in adult concept learning.James Close, Ulrike Hahn, Carl Hodgets & Emmanuel M. Pothos - 2010 - In Denis Mareschal, Paul Quinn & Stephen E. G. Lea (eds.), The Making of Human Concepts. Oxford University Press.
  23.  18
    Theory-neutral system regularity measurements.Patrick Juola, Todd M. Bailey & Emmanuel M. Pothos - 1998 - In Morton Ann Gernsbacher & Sharon J. Derry (eds.), Proceedings of the 20th Annual Conference of the Cognitive Science Society. Lawerence Erlbaum. pp. 555--560.
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  24.  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.
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  25.  20
    Context effects equally applicable in generalization and similarity.Emmanuel M. Pothos - 2001 - Behavioral and Brain Sciences 24 (4):699-700.
    Shepard's theoretical analysis of generalization is assumed to enable an objective measure of the relation between objects, an assumption taken on board by Tenenbaum & Griffiths. I argue that context effects apply to generalization in the same way as they apply to similarity. Thus, the need to extend Shepard's formalism in a way that incorporates context effects should be acknowledged. [Shepard; Tenenbaum & Griffiths].
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  26.  65
    Contingent necessity versus logical necessity in categorisation.Emmanuel M. Pothos, Ulrike Hahn & Mercè Prat-Sala - 2010 - Thinking and Reasoning 16 (1):45 – 65.
    Critical (necessary or sufficient) features in categorisation have a long history, but the empirical evidence makes their existence questionable. Nevertheless, there are some cases that suggest critical feature effects. The purpose of the present work is to offer some insight into why classification decisions might misleadingly appear as if they involve critical features. Utilising Tversky's (1977) contrast model of similarity, we suggest that when an object has a sparser representation, changing any of its features is more likely to lead to (...)
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  27.  43
    Preferring rules to similarity: Coherence, goals, and commitment.Emmanuel M. Pothos - 2005 - Behavioral and Brain Sciences 28 (1):37-49.
    This response to the open peer commentary discusses what should be the appropriate explanatory scope of a rules versus similarity proposal and accordingly evaluates the Rules versus Similarity one. Additionally, coherence, goals, and commitment are presented as inferential notions, fully consistent with the Rules versus Similarity distinction, that allow us to predict when Rules would be preferred to Similarity.
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  28.  72
    Symmetry, repetition, and figural goodness: an investigation of the Weight of Evidence theory.Emmanuel M. Pothos & Robert Ward - 2000 - Cognition 75 (3):B65-B78.
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  29.  29
    Constructive Biases in Clinical Judgment.Bartosz W. Wojciechowski, Bernadetta Izydorczyk, Pawel Blasiak, James M. Yearsley, Lee C. White & Emmanuel M. Pothos - 2022 - Topics in Cognitive Science 14 (3):508-527.
    Topics in Cognitive Science, Volume 14, Issue 3, Page 508-527, July 2022.
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  30.  21
    Corrigendum: Is There a Conjunction Fallacy in Legal Probabilistic Decision Making?Bartosz W. Wojciechowski & Emmanuel M. Pothos - 2018 - Frontiers in Psychology 9.
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  31.  46
    Is There a Conjunction Fallacy in Legal Probabilistic Decision Making?Bartosz W. Wojciechowski & Emmanuel M. Pothos - 2018 - Frontiers in Psychology 9.
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