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1

Introduction to projective cognition: A mathematical approach. New York: Philosophical Library, 1986.

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2

Busemeyer, Jerome R. Quantum models of cognition and decision. Cambridge: Cambridge University Press, 2012.

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3

Busemeyer, Jerome R. Quantum models of cognition and decision. Cambridge: Cambridge University Press, 2012.

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4

Psicologia matematica: Spunti per una modellistica formale dei processi cognitivi. Roma: Aracne, 2006.

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5

Computational models of conditioning. New York: Cambridge University Press, 2010.

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6

Computation, dynamics, and cognition. New York: Oxford University Press, 1997.

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7

Cognitive sciences: Basic problems, new perspectives and implications for artificial intelligence. Orlando: Academic Press, 1986.

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8

Quantum theoretic machines: What is thought from the point of view of physics. Amsterdam: Elsevier, 2000.

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9

Human cognitive abilities: A survey of factor-analytic studies. Cambridge: Cambridge University Press, 1993.

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10

Principles of brain functioning: A synergetic approach to brain activity, behavior, and cognition. Berlin: Springer, 1996.

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11

Khrennikov, A. I︠U︡. Classical and quantum mental models and Freud's theory of unconscious/conscious mind. Växjö, Sweden]: Växjö University Press, 2002.

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12

Forstmann, Birte U., and Eric-Jan Wagenmakers. An introduction to model-based cognitive neuroscience. New York: Springer, 2015.

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13

Applied cognitive psychology: An information-processing framework. London: Methuen, 1988.

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14

Haken, Hermann. Principles of Brain Functioning: A Synergetic Approach to Brain Activity, Behavior and Cognition. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996.

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15

What is thought? Cambridge, MA: MIT Press, 2003.

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16

Garnham, Alan. Mental models as representations of discourse and text. Chichester, West Sussex, England: E. Horwood, 1987.

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17

Eindhoven), Working Models of Human Perception (1987. Working models of human perception. London: Academic, 1989.

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18

Galanter, Eugene. Multiple paths in complex tasks: Technical report PPL 87/4. [Washington, D.C: National Aeronautics and Space Administration, 1987.

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19

Kalechofsky, Robert. The persistence of error: Essays in developmental epistemology. Lanham, MD: University Press of America, 1987.

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20

Images of competitive space: A study of managerial and organizational strategic cognition. Basingstoke, Hampshire: Palgrave Macmillan, 2005.

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21

Computing the mind: How the mind really works. Oxford: Oxford University Press, 2008.

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22

Govindaraj, T. Operator modeling in commercial aviation: Cognitive models, intelligent displays, and pilot's assistants : final report, July 1, 1990 through April 30, 1994. [Washington, DC: National Aeronautics and Space Administration, 1994.

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23

Govindaraj, T. Operator modeling in commercial aviation: Cognitive models, intelligent displays, and pilot's assistants : final report, July 1, 1990 through April 30, 1994. [Washington, DC: National Aeronautics and Space Administration, 1994.

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24

1922-, Williams Carl D., ed. Confirmation learning theory. New York: P. Lang, 1989.

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25

Wyllis, Bandler, ed. Tracing chains-of-thought: Fuzzy methods in cognitive diagnosis. Heidelberg, [Germany]: Physica-Verlag, 1996.

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26

Busemeyer, Jerome R. Cognitive modeling. Thousand Oaks, Calif: Sage Publications, 2009.

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27

Swedish, Conference on Connectionism (1995 Skövde Sweden). Current trends in connectionism: Proceedings of the Swedish Conference on Connectionism, 1995. Hove (UK): L. Erlbaum Associates, 1995.

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28

Houpt, Joseph W., and Leslie M. Blaha. Mathematical Models of Perception and Cognition Volume II. Taylor & Francis Group, 2018.

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29

Houpt, Joseph. Mathematical Models of Perception and Cognition Volume II. Routledge, 2016. http://dx.doi.org/10.4324/9781315647265.

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30

Houpt, Joseph. Mathematical Models of Perception and Cognition Volume I. Psychology Press, 2016. http://dx.doi.org/10.4324/9781315647272.

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31

Houpt, Joseph W., and Leslie M. Blaha. Mathematical Models of Perception and Cognition Volume I. Taylor & Francis Group, 2018.

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32

Busemeyer, Jerome R., and Peter D. Bruza. Quantum Models of Cognition and Decision. Cambridge University Press, 2014.

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33

1947-, Morris Peter E., and International Workshop on Modelling Cognition (1985 : Lancaster University), eds. Modelling cognition. Chichester: Wiley, 1987.

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34

Computational Modeling in Cognition: Principles and Practice. SAGE Publications, Incorporated, 2010.

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35

Townsend, James T., Zheng Wang, Jerome R. Busemeyer, and Ami Eidels. Oxford Handbook of Computational and Mathematical Psychology. Oxford University Press, Incorporated, 2015.

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36

Farrell, Simon. Computational Modeling of Cognition and Behavior. Cambridge University Press, 2018.

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37

Farrell, Simon, and Stephan Lewandowsky. Computational Modeling of Cognition and Behavior. Cambridge University Press, 2018.

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38

Mathematical Principles of Human Conceptual Behavior. Taylor & Francis Group, 2014.

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39

Roberts, Fred S., Peter Theuns, and Cornelia E. Dowling. Recent Progress in Mathematical Psychology: Psychophysics, Knowledge Representation, Cognition, and Measurement. Taylor & Francis Group, 2014.

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40

Houpt, Joseph W., and Leslie M. Blaha. Mathematical Models of Perception and Cognition Volume II: A Festschrift for James T. Townsend. Taylor & Francis Group, 2016.

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41

Baum, Eric B. What Is Thought? (Bradford Books). The MIT Press, 2006.

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42

Baum, Eric B. What Is Thought? (Bradford Books). The MIT Press, 2004.

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43

(Editor), Cornelia E. Dowling, Fred S. Roberts (Editor), and Peter Theuns (Editor), eds. Recent Progress in Mathematical Psychology: Psychophysics, Knowledge Representation, Cognition, and Measurement (Scientific Psychology Series). Lawrence Erlbaum, 1998.

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44

1957-, Boi L., ed. Geometries of nature, living systems and human cognition: New interactions of mathematics with natural sciences and humanities. Singapore: World Scientific, 2005.

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45

Modelling High-level Cognitive Processes. Lawrence Erlbaum, 2002.

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46

Mathematical Principles of Human Conceptual Behavior: The Structural Nature of Conceptual Representation and Processing. Taylor & Francis Group, 2016.

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47

Austerweil, Joseph L., Samuel J. Gershman, and Thomas L. Griffiths. Structure and Flexibility in Bayesian Models of Cognition. Edited by Jerome R. Busemeyer, Zheng Wang, James T. Townsend, and Ami Eidels. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199957996.013.9.

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Probability theory forms a natural framework for explaining the impressive success of people at solving many difficult inductive problems, such as learning words and categories, inferring the relevant features of objects, and identifying functional relationships. Probabilistic models of cognition use Bayes’s rule to identify probable structures or representations that could have generated a set of observations, whether the observations are sensory input or the output of other psychological processes. In this chapter we address an important question that arises within this framework: How do people infer representations that are complex enough to faithfully encode the world but not so complex that they “overfit” noise in the data? We discuss nonparametric Bayesian models as a potential answer to this question. To do so, first we present the mathematical background necessary to understand nonparametric Bayesian models. We then delve into nonparametric Bayesian models for three types of hidden structure: clusters, features, and functions. Finally, we conclude with a summary and discussion of open questions for future research.
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48

Mathematical Models of Perception and Cognition Volume I: A Festschrift for James T. Townsend. Taylor & Francis Group, 2016.

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49

Bayesian Cognitive Modeling: A Practical Course. Cambridge University Press, 2014.

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50

Lee, Michael D., and Eric-Jan Wagenmakers. Bayesian Cognitive Modeling. University of Cambridge ESOL Examinations, 2014.

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