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  1.  14
    Can Strategic Ignorance Explain the Evolution of Love?Adam Bear & David G. Rand - 2019 - Topics in Cognitive Science 11 (2):393-408.
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  2.  8
    Editors' Introduction: Computational Approaches to Social Cognition.Fiery Cushman & Samuel Gershman - 2019 - Topics in Cognitive Science 11 (2):281-298.
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  3.  2
    Introduction to Volume 11, Issue 2 of Topi CS.Wayne D. Gray - 2019 - Topics in Cognitive Science 11 (2):280-280.
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  4.  9
    The Flatland Fallacy: Moving Beyond Low–Dimensional Thinking.Eshin Jolly & Luke J. Chang - 2019 - Topics in Cognitive Science 11 (2):433-454.
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  5.  11
    A Simple Computational Theory of General Collective Intelligence.Peter M. Krafft - 2019 - Topics in Cognitive Science 11 (2):374-392.
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  6.  9
    Information Sampling, Judgment, and the Environment: Application to the Effect of Popularity on Evaluations.Gaël Le Mens, Jerker Denrell, Balázs Kovács & Hülya Karaman - 2019 - Topics in Cognitive Science 11 (2):358-373.
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  7.  5
    Computational Models of Emotion Inference in Theory of Mind: A Review and Roadmap.Desmond C. Ong, Jamil Zaki & Noah D. Goodman - 2019 - Topics in Cognitive Science 11 (2):338-357.
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  8.  4
    Integrating Incomplete Information With Imperfect Advice.Natalia Vélez & Hyowon Gweon - 2019 - Topics in Cognitive Science 11 (2):299-315.
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  9.  4
    A Unifying Computational Framework for Teaching and Active Learning.Scott Cheng‐Hsin Yang, Wai Keen Vong, Yue Yu & Patrick Shafto - 2019 - Topics in Cognitive Science 11 (2):316-337.
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  10.  6
    Modeling Morality in 3‐D: Decision‐Making, Judgment, and Inference.Hongbo Yu, Jenifer Z. Siegel & Molly J. Crockett - 2019 - Topics in Cognitive Science 11 (2):409-432.
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  11.  18
    The Role of the Anterior Cingulate Cortex in Prediction Error and Signaling Surprise.William H. Alexander & Joshua W. Brown - 2019 - Topics in Cognitive Science 11 (1):119-135.
    In the past two decades, reinforcement learning has become a popular framework for understanding brain function. A key component of RL models, prediction error, has been associated with neural signals throughout the brain, including subcortical nuclei, primary sensory cortices, and prefrontal cortex. Depending on the location in which activity is observed, the functional interpretation of prediction error may change: Prediction errors may reflect a discrepancy in the anticipated and actual value of reward, a signal indicating the salience or novelty of (...)
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  12.  7
    Visual Search Without Selective Attention: A Cognitive Architecture Account.David E. Kieras - 2019 - Topics in Cognitive Science 11 (1):222-239.
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  13.  15
    Violations of Core Knowledge Shape Early Learning.Aimee E. Stahl & Lisa Feigenson - 2019 - Topics in Cognitive Science 11 (1):136-153.
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  14.  14
    The Role of Surprise in Learning: Different Surprising Outcomes Affect Memorability Differentially.Meadhbh I. Foster & Mark T. Keane - 2019 - Topics in Cognitive Science 11 (1):75-87.
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  15.  5
    An Integrated Working Memory Model for Time‐Based Resource‐Sharing.Joseph J. Glavan & Joseph W. Houpt - 2019 - Topics in Cognitive Science 11 (1):261-276.
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  16.  8
    Introduction to Volume 11, Issue 1 of topiCS.Wayne D. Gray - 2019 - Topics in Cognitive Science 11 (1):4-6.
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  17.  8
    How Communication Can Make Voters Choose Less Well.Ulrike Hahn, Momme von Sydow & Christoph Merdes - 2019 - Topics in Cognitive Science 11 (1):194-206.
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  18.  7
    Surprise, Recipes for Surprise, and Social Influence.Jeffrey Loewenstein - 2019 - Topics in Cognitive Science 11 (1):178-193.
    Surprising people can provide an opening for influencing them. Surprises garner attention, are arousing, are memorable, and can prompt shifts in understanding. Less noted is that, as a result, surprises can serve to persuade others by leading them to shifts in attitudes. Furthermore, because stories, pictures, and music can generate surprises and those can be widely shared, surprise can have broad social influence. People also tend to share surprising items with others, as anyone on social media has discovered. This means (...)
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  19.  22
    Seeing Patterns in Randomness: A Computational Model of Surprise.Phil Maguire, Philippe Moser, Rebecca Maguire & Mark T. Keane - 2019 - Topics in Cognitive Science 11 (1):103-118.
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  20.  15
    Editors’ Introduction and Review: An Appraisal of Surprise: Tracing the Threads That Stitch It Together.Edward L. Munnich, Meadhbh I. Foster & Mark T. Keane - 2019 - Topics in Cognitive Science 11 (1):37-49.
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  21.  8
    Learning From Surprise: Harnessing a Metacognitive Surprise Signal to Build and Adapt Belief Networks.Edward Munnich & Michael A. Ranney - 2019 - Topics in Cognitive Science 11 (1):164-177.
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  22.  6
    Editors' Introduction: Best Papers From the 2018 International Conference on Cognitive Modeling.Christopher Myers, Joseph Houpt & Ion Juvina - 2019 - Topics in Cognitive Science 11 (1):220-221.
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  23.  23
    The Cognitive‐Evolutionary Model of Surprise: A Review of the Evidence. [REVIEW]Rainer Reisenzein, Gernot Horstmann & Achim Schützwohl - 2019 - Topics in Cognitive Science 11 (1):50-74.
    Research on surprise relevant to the cognitive-evolutionary model of surprise proposed by Meyer, Reisenzein, and Schützwohl is reviewed. The majority of the assumptions of the model are found empirically supported. Surprise is evoked by unexpected events and its intensity is determined by the degree if schema-discrepancy, whereas the novelty and the valence of the eliciting events probably do not have an independent effect. Unexpected events cause an automatic interruption of ongoing mental processes that is followed by an attentional shift and (...)
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  24.  4
    The Role of Dorsal Premotor Cortex in Resolving Abstract Motor Rules: Converging Evidence From Transcranial Magnetic Stimulation and Cognitive Modeling.Patrick Rice & Andrea Stocco - 2019 - Topics in Cognitive Science 11 (1):240-260.
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  25.  9
    Cognitive Success: A Consequentialist Account of Rationality in Cognition.Gerhard Schurz & Ralph Hertwig - 2019 - Topics in Cognitive Science 11 (1):7-36.
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  26.  9
    Another Look at Looking Time: Surprise as Rational Statistical Inference.Zi L. Sim & Fei Xu - 2019 - Topics in Cognitive Science 11 (1):154-163.
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  27.  8
    Color Naming Reflects Both Perceptual Structure and Communicative Need.Noga Zaslavsky, Charles Kemp, Naftali Tishby & Terry Regier - 2019 - Topics in Cognitive Science 11 (1):207-219.
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