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Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations.Joshua C. Peterson, Joshua T. Abbott & Thomas L. Griffiths - 2018 - Cognitive Science 42 (8):2648-2669.details
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The Oxford Handbook of Causal Reasoning.Michael Waldmann (ed.) - 2017 - Oxford, England: Oxford University Press.details
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Tracking word frequency effects through 130 years of sound change.Jennifer B. Hay, Janet B. Pierrehumbert, Abby J. Walker & Patrick LaShell - 2015 - Cognition 139 (C):83-91.details
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Functional kinds: a skeptical look.Cameron Buckner - 2015 - Synthese 192 (12):3915-3942.details
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Word Meanings Evolve to Selectively Preserve Distinctions on Salient Dimensions.Catriona Silvey, Simon Kirby & Kenny Smith - 2015 - Cognitive Science 39 (1):212-226.details
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Attention and reinforcement learning: Constructing representations from indirect feedback.Fabián Canas & Matt Jones - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society.details
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Can semi-supervised learning explain incorrect beliefs about categories?Charles W. Kalish, Timothy T. Rogers, Jonathan Lang & Xiaojin Zhu - 2011 - Cognition 120 (1):106-118.details
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Diagnostic recognition: task constraints, object information, and their interactions.Philippe G. Schyns - 1998 - Cognition 67 (1-2):147-179.details
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Birth of an Abstraction: A Dynamical Systems Account of the Discovery of an Elsewhere Principle in a Category Learning Task.Whitney Tabor, Pyeong W. Cho & Harry Dankowicz - 2013 - Cognitive Science 37 (7):1193-1227.details
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Sampling Assumptions in Inductive Generalization.Daniel J. Navarro, Matthew J. Dry & Michael D. Lee - 2012 - Cognitive Science 36 (2):187-223.details
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Using Variability to Guide Dimensional Weighting: Associative Mechanisms in Early Word Learning.Keith S. Apfelbaum & Bob McMurray - 2011 - Cognitive Science 35 (6):1105-1138.details
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Models and mechanisms in psychological explanation.Daniel A. Weiskopf - 2011 - Synthese 183 (3):313-338.details
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Précis of semantic cognition: A parallel distributed processing approach.Timothy T. Rogers & James L. McClelland - 2008 - Behavioral and Brain Sciences 31 (6):689-714.details
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The role of similarity in categorization: providing a groundwork.Robert L. Goldstone - 1994 - Cognition 52 (2):125-157.details
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Hume and Cognitive Science: The Current Status of the Controversy over Abstract Ideas.Mark Collier - 2005 - Phenomenology and the Cognitive Sciences 4 (2):197-207.details
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Connectionist and diffusion models of reaction time.Roger Ratcliff, Trisha Van Zandt & Gail McKoon - 1999 - Psychological Review 106 (2):261-300.details
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A Rational Analysis of Rule-Based Concept Learning.Noah D. Goodman, Joshua B. Tenenbaum, Jacob Feldman & Thomas L. Griffiths - 2008 - Cognitive Science 32 (1):108-154.details
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What is adaptive about adaptive decision making? A parallel constraint satisfaction account.Andreas Glöckner, Benjamin E. Hilbig & Marc Jekel - 2014 - Cognition 133 (3):641-666.details
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Making Probabilistic Relational Categories Learnable.Wookyoung Jung & John E. Hummel - 2015 - Cognitive Science 39 (6):1259-1291.details
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A probabilistic model of cross-categorization.Patrick Shafto, Charles Kemp, Vikash Mansinghka & Joshua B. Tenenbaum - 2011 - Cognition 120 (1):1-25.details
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The dynamic nature of knowledge: Insights from a dynamic field model of children’s novel noun generalization.Larissa K. Samuelson, Anne R. Schutte & Jessica S. Horst - 2009 - Cognition 110 (3):322-345.details
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Similarity and rules: distinct? exhaustive? empirically distinguishable?Ulrike Hahn & Nick Chater - 1998 - Cognition 65 (2-3):197-230.details
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Two ways of learning associations.Luke Boucher & Zoltán Dienes - 2003 - Cognitive Science 27 (6):807-842.details
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Reward-based distractor interference: associative learning and interference stage.Bing Li - 2021 - Dissertation, Ludwig Maximilians Universität, Münchendetails
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Knowledge effect the selective attention in category learning: An eyetracking study.S. Kim & Bob Rehder - 2009 - In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society. pp. 230--235.details
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Bayesian reverse-engineering considered as a research strategy for cognitive science.Carlos Zednik & Frank Jäkel - 2016 - Synthese 193 (12):3951-3985.details
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An Evolutionary Analysis of Learned Attention.Richard A. Hullinger, John K. Kruschke & Peter M. Todd - 2015 - Cognitive Science 39 (6):1172-1215.details
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Analyzing the factors underlying the structure and computation of the meaning of< em> chipmunk,< em> cherry,< em> chisel,< em> cheese, and< em> cello(and many other such concrete nouns).George S. Cree & Ken McRae - 2003 - Journal of Experimental Psychology: General 132 (2):163.details
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Integrating reinforcement learning with models of representation learning.Matt Jones & Fabián Canas - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 1258--1263.details
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On the Validity of Simulating Stagewise Development by Means of PDP Networks: Application of Catastrophe Analysis and an Experimental Test of Rule‐Like Network Performance.Maartje E. J. Raijmakers, Sylvester Koten & Peter C. M. Molenaar - 1996 - Cognitive Science 20 (1):101-136.details
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PROBabilities from EXemplars (PROBEX): a “lazy” algorithm for probabilistic inference from generic knowledge.Peter Juslin & Magnus Persson - 2002 - Cognitive Science 26 (5):563-607.details
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Theory-based Bayesian models of inductive learning and reasoning.Joshua B. Tenenbaum, Thomas L. Griffiths & Charles Kemp - 2006 - Trends in Cognitive Sciences 10 (7):309-318.details
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Knowledge as Process: Contextually Cued Attention and Early Word Learning.Linda B. Smith, Eliana Colunga & Hanako Yoshida - 2010 - Cognitive Science 34 (7):1287-1314.details
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Adaptationism.Steven Hecht Orzack - 2010 - Stanford Encyclopedia of Philosophy.details
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From implicit skills to explicit knowledge: a bottom‐up model of skill learning.Edward Merrillb & Todd Petersonb - 2001 - Cognitive Science 25 (2):203-244.details
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The rules versus similarity distinction.Emmanuel M. Pothos - 2005 - Behavioral and Brain Sciences 28 (1):1-14.details
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Stipulating versus discovering representations.David C. Plaut & James L. McClelland - 2000 - Behavioral and Brain Sciences 23 (4):489-491.details
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Criteria for the Design and Evaluation of Cognitive Architectures.Sashank Varma - 2011 - Cognitive Science 35 (7):1329-1351.details
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Semiosis in cognitive systems: a neural approach to the problem of meaning. [REVIEW]Eliano Pessa & Graziano Terenzi - 2007 - Mind and Society 6 (2):189-209.details
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You only had to ask me once: Long-term retention requires direct queries during learning.Yasuaki Sakamoto & Bradley C. Love - 2009 - In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society.details
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When learning to classify by relations is easier than by features.Bradley C. Love & Marc T. Tomlinson - 2010 - Thinking and Reasoning 16 (4):372-401.details
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Attentional and representational flexibility of feature inference learning.Aaron B. Hoffman & Bob Rehder - 2009 - In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society. pp. 1864--1869.details
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Reasons to doubt the present evidence for metaphoric representation.G. Murphy - 1997 - Cognition 62 (1):99-108.details
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Accounting for Graded Performance within a Discrete Search Framework.Craig S. Miller & John E. Laird - 1996 - Cognitive Science 20 (4):499-537.details
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Language Evolution by Iterated Learning With Bayesian Agents.Thomas L. Griffiths & Michael L. Kalish - 2007 - Cognitive Science 31 (3):441-480.details
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Human Semi-Supervised Learning.Bryan R. Gibson, Timothy T. Rogers & Xiaojin Zhu - 2013 - Topics in Cognitive Science 5 (1):132-172.details
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From Perceptual Categories to Concepts: What Develops?Vladimir M. Sloutsky - 2010 - Cognitive Science 34 (7):1244-1286.details
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The acquisition of Boolean concepts.Geoffrey P. Goodwin & Philip N. Johnson-Laird - 2013 - Trends in Cognitive Sciences 17 (3):128-133.details
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Learning of rules that have high-frequency exceptions: New empirical data and a hybrid connectionist model.John K. Kruschke & Michael A. Erickson - 1994 - In Ashwin Ram & Kurt Eiselt (eds.), Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society: August 13 to 16, 1994, Georgia Institute of Technology. Erlbaum. pp. 514--519.details
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