Anderson, J. R. (1990) The adaptive character of thought. Erlbaum.
Anderson, J. R. (1991b) The adaptive nature of human categorization. Psychological Review
Anderson, J. R., Bothell, D., Lebiere, C. & Matessa, M. (1998) An integrated theory of list memory. Journal of Memory and Language
Anderson, J. R. & Schooler, L. J. (1991) Reflections of the environment in memory. Psychological Science
Austerweil, J. & Griffiths, T. L. (2008) Analyzing human feature learning as nonparametric Bayesian inference. Advances in Neural Information Processing Systems
Baker, C. L., Saxe, R. & Tenenbaum, J. B. (2009) Action understanding as inverse planning. Cognition
Baldwin, J. D. & Baldwin, J. I. (1977) The role of learning phenomena in the ontogeny of exploration and play. In: Primate bio-social development: Biological, social and ecological determinants, ed. Chevalier-Skolnikoff, S. & Poirer, F. E., p. 343–406. Garland.
Beck, J. M., Ma, W. J., Kiani, R., Hanks, T., Churchland, A. K., Roitman, J., Shadlen, M. N., Latham, P. E. & Pouget, A. (2008) Probabilistic population codes for Bayesian decision making. Neuron
Binmore, K. (2009) Rational decisions. Princeton University Press.
Bjorklund, D. F. & Pellegrini, A. D. (2000) Child development and evolutionary psychology. Child Development
Boucher, L., Palmeri, T. J., Logan, G. D. & Schall, J. D. (2007) Inhibitory control in mind and brain: An interactive race model of countermanding saccades. Psychological Review
Bowlby, J. (1969) Attachment and loss, vol. 1: Attachment. Basic Books.
Brighton, H. & Gigerenzer, G. (2008) Bayesian brains and cognitive mechanisms: Harmony or dissonance? In: Bayesian rationality: The probabilistic approach to human reasoning, ed. Oaksford, M. & Chater, N., p. 189–208. Oxford University Press.
Brown, S. D. & Steyvers, M. (2009) Detecting and predicting changes. Cognitive Psychology
Buller, D. J. (2005) Adapting minds: Evolutionary psychology and the persistent quest for human nature. MIT Press.
Burgess, N. & Hitch, G. J. (1999) Memory for serial order: A network model of the phonological loop and its timing. Psychological Review
Busemeyer, J. R. & Johnson, J. G. (2008) Microprocess models of decision making. In: Cambridge handbook of computational psychology, ed. Sun, R., p. 302–21. Cambridge University Press.
Buss, D. M. (1994) The evolution of desire: Strategies of human mating. Basic Books.
Buss, D. M., Haselton, M. G., Shackelford, T. K., Bleske, A. L. & Wakefield, J. C. (1998) Adaptations, exaptations, and spandrels. American Psychologist
Caramazza, A. & Shelton, J. R. (1998) Domain-specific knowledge systems in the brain: The animate-inanimate distinction. Journal of Cognitive Neuroscience
Chater, N. & Manning, C. D. (2006) Probabilistic models of language processing and acquisition. Trends in Cognitive Sciences
Chater, N. & Oaksford, M. (1999) The probability heuristics model of syllogistic reasoning. Cognitive Psychology
Chater, N. & Oaksford, M. (2008) The probabilistic mind: Prospects for a Bayesian cognitive science. In: The probabilistic mind: Prospects for rational models of cognition, ed. Oaksford, M. & Chater, N., p. 3–31. Oxford University Press.
Chater, N., Oaksford, M., Nakisa, R. & Redington, M. (2003) Fast, frugal, and rational: How rational norms explain behavior. Organizational Behavior and Human Decision Processes
Chater, N., Reali, F. & Christiansen, M. H. (2009) Restrictions on biological adaptation in language evolution. Proceedings of the National Academy of Sciences USA
Chater, N., Tenenbaum, J. & Yuille, A. (2006) Probabilistic models of cognition: Conceptual foundations. Trends in Cognitive Sciences
Chomsky, N. (1959) A review of B. F. Skinner's Verbal Behavior
Clark, D. D. & Sokoloff, L. (1999) Circulation and energy metabolism in the brain. In: Basic neurochemistry: Molecular, cellular and medical aspects, ed. Siegel, G. J., Agranoff, B. W., Albers, R. W., Fisher, S. K. & Uhler, M. D., p. 637–70. Lippincott-Raven.
Clearfield, M. W., Dineva, E., Smith, L. B., Diedrich, F. J. & Thelen, E. (2009) Cue salience and infant perseverative reaching: Tests of the dynamic field theory. Developmental Science
Colunga, E. & Smith, L. (2005) From the lexicon to expectations about kinds: A role for associative learning. Psychological Review
Conati, C., Gertner, A., VanLehn, K. & Druzdzel, M. (1997) On-line student modeling for coached problem solving using Bayesian networks. In: User modeling: Proceedings of the Sixth International Conference, UM97, Berlin, 1997, pp. 231–42, ed. Jameson, A., Paris, C. & Tasso, C.. Springer.
Cosmides, L. & Tooby, J. (1992) Cognitive adaptations for social exchange. In: The adapted mind: Evolutionary psychology and the generation of culture, ed. Barkow, J., Cosmides, L. & Tooby, J.. p. 163–228. Oxford University Press.
Cree, G. S. & McRae, K. (2003) Analyzing the factors underlying the structure and computation of the meaning of chipmunk, cherry, chisel, cheese, and cello (and many other such concrete nouns). Journal of Experimental Psychology: General
Crick, F. (1989) The recent excitement about neural networks. Nature
Czerlinski, J., Gigerenzer, G. & Goldstein, D. G. (1999) How good are simple heuristics? In: Simple heuristics that make us smart, ed. Gigerenzer, G. & Todd, P. M., p. 97–118. Oxford University Press.
Danks, D. (2008) Rational analyses, instrumentalism, and implementations. In: The probabilistic mind: Prospects for Bayesian cognitive science, ed. Oaksford, M. & Chater, N., p. 59–75. Oxford University Press.
Daugman, J. G. (2001) Brain metaphor and brain theory. In: Philosophy and the neurosciences: A reader, ed. Bechtel, W., Mandik, P., Mundale, J. & Stufflebeam, R. S., p. 23–36. Blackwell.
Davis, T. & Love, B. C. (2010) Memory for category information is idealized through contrast with competing options. Psychological Science
Daw, N. & Courville, A. (2007) The pigeon as particle filter. Advances in Neural Information Processing Systems
Daw, N. D., Courville, A. C. & Dayan, P. (2008) Semi-rational models: The case of trial order. In: The probabilistic mind: Prospects for rational models of cognition, ed. Oaksford, M. & Chater, N., p. 431–52. Oxford University Press.
Daw, N. D., Niv, Y. & Dayan, P. (2005) Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control. Nature Neuroscience
Dawes, R. M. & Corrigan, B. (1974) Linear models in decision making. Psychological Bulletin
Dawkins, R. (1987) The blind watchmaker. W. W. Norton.
Denève, S. (2008) Bayesian spiking neurons. I: Inference. Neural Computation
Denève, S., Latham, P. E. & Pouget, A. (1999) Reading population codes: A neural implementation of ideal observers. Nature Neuroscience
Dennis, S. & Humphreys, M. S. (1998) Cuing for context: An alternative to global matching models of recognition memory. In: Rational models of cognition, ed. Oaksford, M. & Chater, N., p. 109–27. Oxford University Press.
Devlin, J. T., Gonnerman, L. M., Andersen, E. S. & Seidenberg, M. S. (1998) Category-specific semantic deficits in focal and widespread brain damage: A computational account. Journal of Cognitive Neuroscience
Dickinson, A. M. (2000) The historical roots of organizational behavior management in the private sector: The 1950s–1980s. Journal of Organizational Behavior Management
Doll, B. B., Jacobs, W. J., Sanfey, A. G. & Frank, M. J. (2009) Instructional control of reinforcement learning: A behavioral and neurocomputational investigation. Brain Research
Doucet, A., Godsill, S. & Andrieu, C. (2000) On sequential Monte Carlo sampling methods for Bayesian filtering. Statistics and Computing
Dunbar, K. (1995) How scientists really reason: Scientific reasoning in real-world laboratories. In: Mechanisms of insight, ed. Sternberg, R. J. & Davidson, J., p. 365–95. MIT Press.
Dyson, F. W., Eddington, A. S. & Davidson, C. (1920) A determination of the deflection of light by the sun's gravitational field, from observations made at the total eclipse of May 29, 1919. Philosophical Transactions of the Royal Society of London, Series A: Mathematical, Physical and Engineering Sciences
Ein-Dor, T., Mikulincer, M., Doron, G. & Shaver, P. R. (2010) The attachment paradox: How can so many of us (the insecure ones) have no adaptive advantages?
Perspectives on Psychological Science
Einstein, A. (1916) Die Grundlage der allgemeinen Relativitätstheorie [The foundation of the generalized theory of relativity]. Annalen der Physik
Elman, J. L. (1990) Finding structure in time. Cognitive Science
Elman, J. L. (1993) Learning and development in neural networks: The importance of starting small. Cognition
Engelfriet, J. & Rozenberg, G. (1997) Node replacement graph grammars. In: Handbook of graph grammars and computing by graph transformation, vol. 1, ed. Rozenberg, G., p. 1–94. World Scientific.
Estes, W. K. (1957) Theory of learning with constant, variable, or contingent probabilities of reinforcement. Psychometrika
Fitelson, B. (1999) The plurality of Bayesian measures of confirmation and the problem of measure sensitivity. Philosophy of Science
Fodor, J. A. & Pylyshyn, Z. (1988) Connectionism and cognitive architecture: A critical analysis. Cognition
Frank, M. J., Seeberger, L. & O'Reilly, R. C. (2004) By carrot or by stick: Cognitive reinforcement learning in Parkinsonism. Science
Gabbay, D., Hogger, C. & Robinson, J., eds. (1994) Handbook of logic in artificial intelligence and logic programming, vol. 3: Nonmonotonic reasoning and uncertain reasoning. Oxford University Press.
Geisler, W. S. & Diehl, R. L. (2003) A Bayesian approach to the evolution of perceptual and cognitive systems. Cognitive Science
Geisler, W. S., Perry, J. S., Super, B. J. & Gallogly, D. P. (2001) Edge co-occurrence in natural images predicts contour grouping performance. Vision Research
Geman, S., Bienenstock, E. & Doursat, R. (1992) Neural networks and the bias/variance dilemma. Neural Computation
Geman, S. & Geman, D. (1984) Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence
Gentner, D. (1983) Structure-mapping: A theoretical framework for analogy. Cognitive Science
Gentner, D., Brem, S., Ferguson, R. W., Markman, A. B., Levidow, B. B., Wolff, P. & Forbus, K. D. (1997) Analogical reasoning and conceptual change: A case study of Johannes Kepler. Journal of the Learning Sciences
Gibson, J. J. (1979) The ecological approach to visual perception. Houghton Mifflin.
Gigerenzer, G. & Brighton, H. (2009) Homo heuristicus: Why biased minds make better inferences. Topics in Cognitive Science
Gigerenzer, G. & Todd, P. M. (1999) Simple heuristics that make us smart. Oxford University Press.
Gold, J. I. & Shadlen, M. N. (2001) Neural computations that underlie decisions about sensory stimuli. Trends in Cognitive Sciences
Goodman, N. D., Baker, C. L., Bonawitz, E. B., Mansinghka, V. K., Gopnik, A., Wellman, H., Schulz, L. E. & Tenenbaum, J. B. (2006) Intuitive theories of mind: A rational approach to false belief. In: Proceedings of the Twenty-Eighth Annual Conference of the Cognitive Science Society, Vancouver, Canada, ed. Sun, R., p. 1382–87. Cognitive Science Society.
Goodman, N. D., Tenenbaum, J. B., Feldman, J. & Griffiths, T. L. (2008b) A rational analysis of rule-based concept learning. Cognitive Science
Gottlieb, G. (1992) Individual development and evolution: The genesis of novel behavior. Oxford University Press.
Gould, S. J. & Lewontin, R. (1979) The spandrels of San Marco and the Panglossian paradigm: A critique of the adaptationist programme. Proceedings of the Royal Society of London Series B: Biological Sciences
Green, D. M. & Swets, J. A. (1966) Signal detection theory and psychophysics. John Wiley.
Griffiths, T. L. & Ghahramani, Z. (2006) Infinite latent feature models and the Indian buffet process. In: Advances in neural information processing systems, vol. 18, ed. Weiss, J., Schölkopf, B. & Platt, J., p. 475–82. MIT Press.
Griffiths, T. L., Sanborn, A. N., Canini, K. R. & Navarro, D. J. (2008b) Categorization as nonparametric Bayesian density estimation. In: The probabilistic mind: Prospects for rational models of cognition, ed. Oaksford, M. & Chater, N.. Oxford University Press.
Griffiths, T. L., Steyvers, M. & Tenenbaum, J. B. (2007) Topics in semantic representation. Psychological Review
Griffiths, T. L. & Tenenbaum, J. B. (2006) Optimal predictions in everyday cognition. Psychological Science
Griffiths, T. L. & Tenenbaum, J. B. (2009) Theory-based causal induction. Psychological Review
Guttman, N. & Kalish, H. I. (1956) Discriminability and stimulus generalization. Journal of Experimental Psychology
Hamilton, W. D. (1964) The genetical theory of social behavior. Journal of Theoretical Biology
Hastings, W. K. (1970) Monte Carlo sampling methods using Markov chains and their applications. Biometrika
Hebb, D. O. (1949) The organization of behavior: A neuropsychological theory. John Wiley.
Hogarth, R. M. & Karelaia, N. (2005) Ignoring information in binary choice with continuous variables: When is less “more”?
Journal of Mathematical Psychology
Horgan, J. (1999) The undiscovered mind: How the human brain defies replication, medication, and explanation. Psychological Science
Hornik, K., Stinchcombe, M. & White, H. (1989) Multilayer feedforward networks are universal approximators. Neural Networks
Huber, D. E., Shiffrin, R. M., Lyle, K. B. & Ruys, K. I. (2001) Perception and preference in short-term word priming. Psychological Review
Hummel, J. E. & Biederman, I. (1992) Dynamic binding in a neural network for shape recognition. Psychological Review
Jaynes, E. T. (1968) Prior probabilities. IEEE Transactions on Systems Science and Cybernetics
Jeffreys, H. (1946) An invariant form for the prior probability in estimation problems. Proceedings of the Royal Society of London Series A: Mathematical, Physical and Engineering Sciences
Joanisse, M. F. & Seidenberg, M. S. (1999) Impairments in verb morphology after brain injury: A connectionist model. Proceedings of the National Academy of Sciences USA
Joanisse, M. F. & Seidenberg, M. S. (2003) Phonology and syntax in specific language impairment: Evidence from a connectionist model. Brain and Language
Johnson, M. H. (1998) The neural basis of cognitive development. In: Handbook of child psychology, vol. 2: Cognition, perception, and language, ed. Kuhm, D. & Siegler, R. S., p. 1–49. Wiley.
Jones, M. & Sieck, W. R. (2003) Learning myopia: An adaptive recency effect in category learning. Journal of Experimental Psychology: Learning, Memory, and Cognition
Jones, M. & Zhang, J. (2003) Which is to blame: Instrumental rationality, or common knowledge?
Behavioral and Brain Sciences
Kant, I. (1787/1961) Critique of pure reason, trans. Smith, N. K.. St. Martin's Press. (Original work published in 1787).
Kemp, C. & Tenenbaum, J. B. (2008) The discovery of structural form. Proceedings of the National Academy of Sciences USA
Kemp, C., Perfors, A. & Tenenbaum, J. B. (2007) Learning overhypotheses with hierarchical Bayesian models. Developmental Science
Köver, H., Bao, S. (2010) Cortical plasticity as a mechanism for storing Bayesian priors in sensory perception. PLoS ONE
Krugman, P. (2009) How did economists get it so wrong?
New York Times, MM36, September 2.
Kurz, E. M. & Tweney, R. D. (1998) The practice of mathematics and science: From calculus to the clothesline problem. In: Rational models of cognition, ed. Oaksford, M. & Chater, N., p. 415–38. Oxford University Press.
Lee, M. D. & Sarnecka, B. W. (2010) A model of knower-level behavior in number-concept development. Cognitive Science
Love, B. C. (2002) Comparing supervised and unsupervised category learning. Psychonomic Bulletin and Review
Lucas, C., Griffiths, T. L., Xu, F. & Fawcett, C. (2009) A rational model of preference learning and choice prediction by children. Advances in Neural Information Processing Systems
Luce, R. D. (1963) Detection and recognition. In: Handbook of mathematical psychology, ed. Luce, R. D., Bush, R. R. & Galanter, E., p. 103–89. John Wiley.
Machery, E. & Barrett, C. (2006) Debunking adapting minds. Philosophy of Science
Marcus, G. F. (1998) Rethinking eliminative connectionism. Cognitive Psychology
Marcus, G. F. (2008) Kluge: The haphazard construction of the human mind. Houghton Mifflin.
Markman, A. B. & Ross, B. H. (2003) Category use and category learning. Psychological Bulletin
Marr, D. (1982) Vision: A computational investigation into the human representation and processing of visual information. W. H. Freeman.
Mayr, E. (1982) The growth of biological thought: Diversity, evolution, and inheritance. Harvard University Press.
McClelland, J. L., Rumelhart, D. E. & the PDP Research Group. (1986) Parallel distributed processing: Explorations in the microstructure of cognition. Vol. 2: Psychological and biological models. MIT Press.
McCulloch, W. & Pitts, W. (1943) A logical calculus of the ideas immanent in nervous activity. Bulletin of Mathematical Biophysics
McKenzie, C. R. M. & Mikkelsen, L. A. (2007) A Bayesian view of covariation assessment. Cognitive Psychology
McNamara, J. M. & Houston, A. I. (2009) Integrating function and mechanism. Trends in Ecology and Evolution
Michaels, C. F. & Carello, C. (1981) Direct perception. Prentice-Hall.
Miller, E. K. & Cohen, J. D. (2001) An integrative theory of prefrontal cortex function. Annual Review of Neuroscience
Miller, G. A. (2003) The cognitive revolution: A historical perspective. Trends in Cognitive Sciences
Minsky, M. & Papert, S. A. (1969) Perceptrons: An introduction to computational geometry. MIT Press.
Mortimer, D., Feldner, J., Vaughan, T., Vetter, I., Pujic, Z., Rosoff, W. J., Burrage, K., Dayan, P., Richards, L. J. & Goodhill, G. J. (2009) Bayesian model predicts the response of axons to molecular gradients. Proceedings of the National Academy of Sciences USA
Mozer, M. C., Pashler, H. & Homaei, H. (2008) Optimal predictions in everyday cognition: The wisdom of individuals or crowds?
Murphy, G. L. (1993) A rational theory of concepts. Psychology of Learning and Motivation
Nersessian, N. J. (1986) A cognitive-historical approach to meaning in scientific theories. In: The process of science: Contemporary philosophical approaches to understanding scientific practice, ed. Nersessian, N. J.. Martinus Nijhoff.
Newell, A. & Simon, H. A. (1972) Human problem solving. Prentice-Hall.
Newport, E. L. (1990) Maturational constraints on language learning. Cognitive Science
Nosofsky, R. M., Palmeri, T. J. & Mckinley, S. C. (1994) Rule-plus-exception model of classification learning. Psychological Review
Oaksford, M. & Chater, N. (1994) A rational analysis of the selection task as optimal data selection. Psychological Review
Oaksford, M. & Chater, N. (1998a) An introduction to rational models of cognition. In: Rational models of cognition, ed. Oaksford, M. & Chater, N., p. 1–18. Oxford University Press.
Oaksford, M. & Chater, N. (2007) Bayesian rationality: The probabilistic approach to human reasoning. Oxford University Press.
Oaksford, M. & Chater, N. (2010) Conditionals and constraint satisfaction: Reconciling mental models and the probabilistic approach? In: Cognition and conditionals: Probability and logic in human thinking, ed. Oaksford, M. & Chater, N., p. 309–34. Oxford University Press.
Oppenheim, R. W. (1981) Ontogenetic adaptations and retrogressive processes in the development of the nervous system and behavior. In: Maturation and development: Biological and psychological perspectives, ed. Connolly, K. J. & Prechtl, H. F. R., p. 73–108. International Medical.
Pinker, S. (1995) The language instinct: How the mind creates language. Perennial.
Pinker, S. (2002) The blank slate: The modern denial of human nature. Viking.
Pinker, S. & Prince, A. (1988) On language and connectionism: Analysis of a parallel distributed processing model of language acquisition. Cognition
Pitt, M. A., Myung, I. J. & Zhang, S. (2002) Toward a method of selecting among computational models of cognition. Psychological Review
Plaut, D. C., McClelland, J. L., Seidenberg, M. S. & Patterson, K. (1996) Understanding normal and impaired word reading: Computational principles in quasi-regular domains. Psychological Review
Pollack, J. B. (1990) Recursive distributed representations. Artificial Intelligence
Pothos, E. M. & Chater, N. (2002) A simplicity principle in unsupervised human categorization. Cognitive Science
Rachman, S. (1997) The evolution of cognitive behaviour therapy. In: Science and practice of cognitive behaviour therapy, ed. Clark, D., Fairburn, C. G. & Gelder, M. G., p. 1–26. Oxford University Press.
Raiffa, H. & Schlaifer, R (1961) Applied statistical decision theory. Harvard University Press.
Ramscar, M., Yarlett, D., Dye, M., Denny, K. & Thorpe, K. (2010) The effects of feature-label-order and their implications for symbolic learning. Cognitive Science
Ravi, S. & Knight, K. (2009) Minimized models for unsupervised part-of-speech tagging. In: Proceedings of the Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics (ACL) and the 4th International Joint Conference on Natural Language Processing of the AFNLP, ed. Su, K.-Y., p. 504–12. Association for Computational Linguistics. Available at: http://www.aclweb.org/anthology-new/P/P09/P09-1057.pdf
Ricci, G. & Levi-Civita, T. (1900) Méthodes de calcul différentiel absolu et leurs applications [Methods of absolute differential calculus and their applications]. Mathematische Annalen
Rogers, T. T. & Plaut, D. C. (2002) Connectionist perspectives on category-specific deficits. In: Category-specificity in brain and mind, ed. Forde, E. & Humphreys, G. W., p. 251–89. Psychology Press.
Rosch, E. (1978) Principles of categorization. In: Cognition and categorization, ed. Rosch, E. & Lloyd, B. B., p. 27–48. Erlbaum.
Rosenblatt, F. (1962) Principles of neurodynamics: Perceptrons and the theory of brain mechanisms. Spartan Books.
Rougier, N. P., Noelle, D., Braver, T. S., Cohen, J. D. & O'Reilly, R. C. (2005) Prefrontal cortex and the flexibility of cognitive control: Rules without symbols. Proceedings of the National Academy of Sciences USA
Rumelhart, D. E., Hinton, G. E. & Williams, R. J. (1986) Learning representations by back-propagating errors. Nature
Rumelhart, D. E., McClelland, J. L. & the PDP research group. (1986) Parallel distributed processing: Explorations in the microstructure of cognition. Vol. 1: Foundations. MIT Press.
Sakamoto, Y., Jones, M. & Love, B. C. (2008) Putting the psychology back into psychological models: Mechanistic versus rational approaches. Memory and Cognition
Sanborn, A. N., Griffiths, T. L. & Navarro, D. J. (2010a) Rational approximations to rational models: Alternative algorithms for category learning. Psychological Review
Sanborn, A. N., Griffiths, T. L. & Shiffrin, R. M. (2010b) Uncovering mental representations with Markov chain Monte Carlo. Cognitive Psychology
Sargent, T. J. (1993) Bounded rationality in macroeconomics. Oxford University Press.
Savage, L. J. (1954) The foundations of statistics. John Wiley/Dover.
Schwarz, G. E. (1978) Estimating the dimension of a model. Annals of Statistics
Shafto, P., Kemp, C., Mansinghka, V. M. & Tenenbaum, J. B. (2011) A probablistic model of cross-categorization. Cognition. 120:1–25.
Shiffrin, R. M. & Steyvers, M. (1998) The effectiveness of retrieval from memory. In: Rational models of cognition, ed. Oaksford, M. & Chater, N., p. 73–95. Oxford University Press.
Simon, H. A. (1957a) A behavioral model of rational choice. In: Models of man, social and rational: Mathematical essays on rational human behavior in a social setting, ed. Simon, H. A., p. 241–60. John Wiley.
Skinner, B. F. (1938) The behavior of organisms: An experimental analysis. Appleton-Century.
Skinner, B. F. (1957) Verbal behavior. Appleton-Century-Crofts.
Skinner, B. F. (1958) Reinforcement today. American Psychologist
Sloman, S. A. & Fernbach, P. M. (2008) The value of rational analysis: An assessment of causal reasoning and learning. In: The probabilistic mind: Prospects for rational models of cognition, ed. Chater, N. & Oaksford, M, p. 485–500. Oxford University Press.
Smith, D. L. (2007) Beyond Westemarck: Can shared mothering or maternal phenotype matching account for incest avoidance?
Smith, L. B., Jones, S. S., Landau, B., Gershkoff-Stowe, L. & Samuelson, L. (2002) Object name learning provides on-the-job training for attention. Psychological Science
Smith, P. K. (1982) Does play matter? Functional and evolutionary aspects of animal and human play. Behavioral and Brain Sciences
Smolensky, P. (1988) On the proper treatment of connectionism. Behavioral and Brain Sciences
Smolin, L. (2006) The trouble with physics: The rise of string theory, the fall of a science, and what comes next. Houghton Mifflin Harcourt.
Sobel, D. M., Tenenbaum, J. B. & Gopnik, A. (2004) Children's causal inferences from indirect evidence: Backwards blocking and Bayesian reasoning in preschoolers. Cognitive Science
Soltani, A. & Wang, X.-J. (2010) Synaptic computation underlying probabilistic inference. Nature Neuroscience
Spencer, J. P., Perone, S. & Johnson, J. S. (2009) The dynamic field theory and embodied cognitive dynamics. In: Toward a unified theory of development: Connectionism and dynamic systems theory reconsidered, ed. Spencer, J. P., Thomas, M. S. & McClelland, J. L., p. 86–118. Oxford University Press.
Sperber, D. & Hirschfeld, L. A. (2003) The cognitive foundations of cultural stability and diversity. Trends in Cognitive Sciences
Stankiewicz, B. J., Legge, G. E., Mansfield, J. S. & Schlicht, E. J. (2006) Lost in virtual space: Studies in human and ideal spatial navigation. Journal of Experimental Psychology: Human Perception and Performance
Steyvers, M., Lee, M. D. & Wagenmakers, E.-J. (2009) A Bayesian analysis of human decision-making on bandit problems. Journal of Mathematical Psychology
Steyvers, M., Tenenbaum, J. B., Wagenmakers, E.-J. & Blum, B. (2003) Inferring causal networks from observations and interventions. Cognitive Science
Stigler, S. M. (1961) The economics of information. Journal of Political Economy
Tenenbaum, J. B. & Griffiths, T. L. (2001) Generalization, similarity, and Bayesian inference. Behavioral and Brain Sciences
Tenenbaum, J. B., Griffiths, T. L. & Kemp, C. (2006) Theory-based Bayesian models of inductive learning and reasoning. Trends in Cognitive Sciences
Thagard, P. (1989) Explanatory coherence. Behavioral and Brain Sciences
Thaler, R. H. & Sunstein, C. R. (2008) Nudge: Improving decisions about health, wealth, and happiness. Yale University Press.
Thibaux, R. & Jordan, M. I. (2007) Hierarchical beta processes and the Indian buffet process. In: Proceedings of the Tenth Conference on Artificial Intelligence and Statistics (AISTATS), ed. Meila, M. & Shen, X.. Society for Artificial Intelligence and Statistics. (Online Publication). Available at: http://www.stat.umn.edu/%7Eaistat/proceedings/start.htm
Thompson-Schill, S., Ramscar, M. & Chrysikou, M. (2009) Cognition without control: When a little frontal lobe goes a long way. Current Directions in Psychological Science
Tooby, J. & Cosmides, L. (2005) Conceptual foundations of evolutionary psychology. In: The handbook of evolutionary psychology, ed. Buss, D. M., p. 5–67. Wiley.
Tversky, A. & Kahneman, D. (1974) Judgment under uncertainty: Heuristics and biases. Science
Vul, E., Frank, M. C., Alvarez, G. A. & Tenenbaum, J. B. (2009) Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model. Advances in Neural Information Processing Systems
Watson, J. B. (1913) Psychology as the behaviorist views it. Psychological Review
Wertheimer, M. (1923/1938) Laws of organization in perceptual forms. In: A source book of Gestalt psychology, ed. & trans. Ellis, W., p. 71–88. Routledge & Kegan Paul. (Original work published in 1923).
Wilder, M. H., Jones, M. & Mozer, M. C. (2009) Sequential effects reflect parallel learning of multiple environmental regularities. Advances in Neural Information Processing Systems
Woit, P. (2006) Not even wrong: The failure of string theory and the search for unity in physical law. Basic Books.
Wolpert, D. (1996) The lack of a priori distinctions between learning algorithms. Neural Computation
Wood, J. N. & Grafman, J. (2003) Human prefrontal cortex: Processing and representational perspectives. Nature Reviews: Neuroscience
Xu, F. & Tenenbaum, J. B. (2007b) Word learning as Bayesian inference. Psychological Review
Yamauchi, T. & Markman, A. B. (1998) Category learning by inference and classification. Journal of Memory and Language
Yu, A. & Cohen, J. (2008) Sequential effects: Superstition or rational behavior?
Advances in Neural Information Processing Systems