Psychonomic Bulletin & Review

, Volume 21, Issue 1, pp 23–46

A taxonomy of inductive problems

Theoretical Review

Abstract

Inductive inferences about objects, features, categories, and relations have been studied for many years, but there are few attempts to chart the range of inductive problems that humans are able to solve. We present a taxonomy of inductive problems that helps to clarify the relationships between familiar inductive problems such as generalization, categorization, and identification, and that introduces new inductive problems for psychological investigation. Our taxonomy is founded on the idea that semantic knowledge is organized into systems of objects, features, categories, and relations, and we attempt to characterize all of the inductive problems that can arise when these systems are partially observed. Recent studies have begun to address some of the new problems in our taxonomy, and future work should aim to develop unified theories of inductive reasoning that explain how people solve all of the problems in the taxonomy.

Keywords

Induction Semantic cognition Generalization Categorization Discovery Identification Reasoning 

References

  1. Aamodt, A., & Plaza, E. (1994). Case-based reasoning: Foundational issues, methodological variations, and system approaches. AI Communications, 7, 39–59.Google Scholar
  2. Adelson, E. H., & Bergen, J. R. (1991). The plenoptic function and the elements of early vision. In M. Landy & J. A. Movshon (Eds.), Computational models of visual processing (pp. 3–20). Cambridge, MA: MIT Press.Google Scholar
  3. Ahn, W.-K., & Medin, D. L. (1992). A two-stage model of category construction. Cognitive Science, 16, 81–121.Google Scholar
  4. Anderson, A. L., Ross, B. H., & Chin-Parker, S. (2002). A further investigation of category learning by inference. Memory & Cognition, 30, 119–128. doi:10.3758/BF03195271 Google Scholar
  5. Anderson, J. R. (1991). The adaptive nature of human categorization. Psychological Review, 98, 409–429. doi:10.1037/0033-295X.98.3.409 Google Scholar
  6. Anderson, J. R., & Fincham, J. M. (1996). Categorization and sensitivity to correlation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22, 259–277. doi:10.1037/0278-7393.22.2.259 PubMedGoogle Scholar
  7. Ashby, F. G., & Maddox, W. T. (1998). Stimulus categorization. In M. H. Birnbaum (Ed.), Handbook of perception and cognition: Judgment, decision making and measurement (pp. 251–301). San Diego, CA: Academic Press.Google Scholar
  8. Austerweil, J. L., & Griffiths, T. L. (2009). Analyzing human feature learning as nonparametric Bayesian inference. In D. Koller, D. Schuurmans, Y. Bengio, & L. Bottou (Eds.), Advances in neural information processing systems 21 (pp. 97–104). Cambridge, MA: MIT Press.Google Scholar
  9. Austerweil, J. L., & Griffiths, T. L. (2011). A rational model of the effects of distributional information on feature learning. Cognitive Psychology, 4, 173–209. doi:10.1016/j.cogpsych.2011.08.002 Google Scholar
  10. Berlin, B., Breedlove, D. E., & Raven, P. H. (1974). Principles of Tzeltal plant classification: An introduction to the botanical ethnography of a Mayan-speaking people of highland Chiapas. New York: Academic Press.Google Scholar
  11. Bisanz, J., Bisanz, G. L., & Korpan, C. A. (1994). Inductive reasoning. In R. J. Sternberg (Ed.), Thinking and Problem Solving. Academic Press.Google Scholar
  12. Bloom, P. (2000). How children learn the meanings of words. Cambridge, MA: MIT Press.Google Scholar
  13. Bower, T. G. R. (1974). Development in infancy. San Francisco: W. H. Freeman.Google Scholar
  14. Braun-Lamesch, M. M. (1962). Le rôle du contexte dans la compréhension du langage chez l’enfant. Psychologie Française, 7, 180–89.Google Scholar
  15. Brown, J. S. (1965). Generalization and discrimination. In D. I. Mostofsky (Ed.), Stimulus generalization (pp. 7–23). Stanford, CA: Stanford University Press.Google Scholar
  16. Brown, S. D., Marley, A. A. J., Donkin, C., & Heathcote, A. (2008). An integrated model of choices and response times in absolute identification. Psychological Review, 115, 396–425. doi:10.1037/0033-295X.115.2.396 PubMedGoogle Scholar
  17. Bruner, J. A., Goodnow, J. S., & Austin, G. J. (1956). A study of thinking. New York, NY: Wiley.Google Scholar
  18. Burke, L. (1952). On the tunnel effect. Quarterly Journal of Experimental Psychology, 4, 121–138.Google Scholar
  19. Carey, S. (1985). Conceptual change in childhood. Cambridge, MA: MIT Press.Google Scholar
  20. Carey, S., & Bartlett, E. (1978). Acquiring a single new word. Papers and Reports on Child Language Development, 15, 17–29.Google Scholar
  21. Carlson, G. (2010). Generics and concepts. In F. J. Pelletier (Ed.), Kinds, things, and stuff: Mass terms and generics (pp. 16–35). New York, NY: Oxford University Press.Google Scholar
  22. Carroll, C. D., & Kemp, C. (2012). Object discovery and inverse physical reasoning. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. 180–185). Austin, TX: Cognitive Science Society.Google Scholar
  23. Chater, N., Oaksford, M., Hahn, U., & Heit, E. (2011). Inductive logic and empirical psychology. In D. M. Gabbay, S. Hartmann, & J. Woods (Eds.), Handbook of the history of logic. Vol. 10: Inductive logic (pp. 553–624). Amsterdam, The Netherlands: North Holland.Google Scholar
  24. Chater, N., Vitanyi, P. M. B., & Stewart, N. (2001). Universal generalization and universal inter-item confusability. Behavioral and Brain Sciences, 24, 659–660.Google Scholar
  25. Christie, S., & Gentner, D. (2010). Where hypotheses come from: Learning new relations by structural alignment. Journal of Cognition and Development, 11, 356–373.Google Scholar
  26. Cohen, L. B., Gelber, E. R., & Lazar, M. A. (1971). Infant habituation and generalization to differing degrees of stimulus novelty. Journal of Experimental Child Psychology, 11, 379–389.PubMedGoogle Scholar
  27. Colberg, M., Nester, M. A., & Trattner, M. H. (1985). Convergence of the inductive and deductive models in the measurement of reasoning abilities. Journal of Applied Psychology, 70, 681–694.Google Scholar
  28. Courville, A. C., Daw, N. D., & Touretzky, D. S. (2006). Bayesian theories of conditioning in a changing world. Trends in Cognitive Sciences, 10, 294–300. doi:10.1016/j.tics.2006.05.004 PubMedGoogle Scholar
  29. Csibra, G., & Volein, A. (2008). Infants can infer the presence of hidden objects from referential gaze information. British Journal of Developmental Psychology, 26, 1–11.Google Scholar
  30. Deverett, B., & Kemp, C. (2012). Learning deterministic causal networks from observational data. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. 288–293). Austin, TX: Cognitive Science Society.Google Scholar
  31. Doumas, L. A. A., Hummel, J. E., & Sandhofer, C. M. (2008). A theory of the discovery and predication of relational concepts. Psychological Review, 115, 1–43. doi:10.1037/0033-295X.115.1.1 PubMedGoogle Scholar
  32. Ennis, D. M. (1988). Confusable and discriminable stimuli: Comment on Nosofsky (1986) and Shepard (1986). Journal of Experimental Psychology: General, 117, 408–411.Google Scholar
  33. Estes, W. K. (1994). Classification and cognition. New York, NY: Oxford University Press.Google Scholar
  34. Fischer, P., & Zytkow, J. M. (1992). Incremental generation and exploration of hidden structure. In J. M. Żytkow (Ed.), Proceedings of the ML-92 Workshop on Machine Discovery (pp. 103–110). Wichita, KS: National Institute for Aviation Research.Google Scholar
  35. Fisher, D. H. (1987). Knowledge acquisition via incremental conceptual clustering. Machine Learning, 2, 139–172.Google Scholar
  36. Fodor, J. A. (1975). The language of thought. Cambridge, MA: Harvard University Press.Google Scholar
  37. Gelman, S. A. (2003). The essential child: Origins of essentialism in everyday thought. Oxford, UK: Oxford University Press.Google Scholar
  38. Gelman, S. A., & Markman, E. M. (1986). Categories and induction in young children. Cognition, 23, 183–209.PubMedGoogle Scholar
  39. Gelman, S. A., & Markman, E. M. (1987). Young children’s inductions from natural kinds: The role of categories and appearances. Child Development, 58, 1532–1541.Google Scholar
  40. Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy. Cognitive Science, 7, 155–170.Google Scholar
  41. Gentner, D., & Kurtz, K. (2005). Relational categories. In W. Ahn, R. L. Goldstone, B. C. Love, A. B. Markman, & P. Wolff (Eds.), Categorization inside and outside the lab: Essays in honor of Douglas L. Medin (pp. 151–175). Washington, DC: American Psychological Association.Google Scholar
  42. Gentner, D., Rattermann, M. J., Markman, A. B., & Kotovsky, L. (1995). Two forces in the development of relational similarity. In T. J. Simon & G. S. Halford (Eds.), Developing cognitive competence: New approaches to process modeling (pp. 263–313). Hillsdale, NJ: Erlbaum.Google Scholar
  43. Gick, M. L., & Holyoak, K. J. (1983). Schema induction and analogical transfer. Cognitive Psychology, 15, 1–38. doi:10.1016/0010-0285(83)90002-6 Google Scholar
  44. Gluck, M. A. (1991). Stimulus generalization and representation in adaptive network models of category learning. Psychological Science, 2, 50–55.Google Scholar
  45. Glymour, C. (2001). The mind’s arrows: Bayes nets and graphical causal models in psychology. Cambridge, MA: MIT Press.Google Scholar
  46. Goodman, J. C., McDonough, L., & Brown, N. N. (1998). The role of semantic context and memory in the acquisition of novel nouns. Child Development, 69, 1330–1344.PubMedGoogle Scholar
  47. Goodman, N. D., Tenenbaum, J. B., Feldman, J., & Griffiths, T. L. (2008). A rational analysis of rule-based concept learning. Cognitive Science, 32, 108–154.PubMedGoogle Scholar
  48. Gopnik, A., & Meltzoff, A. N. (1997). Words, thoughts, and theories. Cambridge, MA: MIT Press.Google Scholar
  49. Griffiths, T. L., & Tenenbaum, J. B. (2005). Structure and strength in causal induction. Cognitive Psychology, 51, 354–384. doi:10.1016/j.cogpsych.2005.05.004 Google Scholar
  50. Guttman, N., & Kalish, H. I. (1956). Discriminability and stimulus generalization. Journal of Experimental Psychology, 51, 79–88.PubMedGoogle Scholar
  51. Hadjichristidis, C., Sloman, S., Stevenson, R., & Over, D. (2004). Feature centrality and property induction. Cognitive Science, 28, 45–74.Google Scholar
  52. Hahn, U., & Chater, N. (1998). Similarity and rules: Distinct? exhaustive? empirically distinguishable? Cognition, 65, 197–230.PubMedGoogle Scholar
  53. Halford, G. S., Wilson, W. H., & Phillips, W. (1998). Processing capacity defined by relational complexity: Implications for comparative, developmental and cognitive psychology. Behavioral and Brain Sciences, 21, 803–831.PubMedGoogle Scholar
  54. Hayes, B. K., Fritz, K., & Heit, E. (2013). The relationship between memory and inductive reasoning: Does it develop? Developmental Psychology, 49, 848–860.PubMedGoogle Scholar
  55. Hayes, B. K., Heit, E., & Swendsen, H. (2010). Inductive reasoning. Wiley Interdisciplinary Reviews: Cognitive Science, 1, 278–292. doi:10.1002/wcs.44 Google Scholar
  56. Hayes, B. K., & Thompson, S. P. (2007). Causal relations and feature similarity in children’s inductive reasoning. Journal of Experimental Psychology: General, 136, 470–484.Google Scholar
  57. Heibeck, T., & Markman, E. (1987). Word learning in children: An examination of fast mapping. Child Development, 58, 1021–1024.PubMedGoogle Scholar
  58. Heit, E. (1998). A Bayesian analysis of some forms of inductive reasoning. In M. Oaksford & N. Chater (Eds.), Rational models of cognition (pp. 248–274). Oxford, UK: Oxford University Press.Google Scholar
  59. Heit, E. (2000). Properties of inductive reasoning. Psychonomic Bulletin & Review, 7, 569–592. doi:10.3758/BF03212996 Google Scholar
  60. Heit, E. (2007). What is induction and why study it? In A. Feeney & E. Heit (Eds.), Inductive reasoning: Experimental, developmental and computational approaches (pp. 1–24). Cambridge, UK: Cambridge University Press.Google Scholar
  61. Heit, E. (2008). Models of inductive reasoning. In R. Sun (Ed.), The Cambridge handbook of computational psychology (pp. 322–338). Cambridge, UK: Cambridge University Press.Google Scholar
  62. Heit, E., Rotello, C. M., & Hayes, B. K. (2012). Relations between memory and reasoning. In B. H. Ross (Ed.), The psychology of learning and motivation (Vol. 57) (pp. 57–101). San Diego, CA: Academic Press.Google Scholar
  63. Heit, E., & Rubinstein, J. (1994). Similarity and property effects in inductive reasoning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 411–422.PubMedGoogle Scholar
  64. Holland, J. H., Holyoak, K. J., Nisbett, R. E., & Thagard, P. R. (1986). Induction: Processes of inference, learning and discovery. Cambridge, MA: MIT Press.Google Scholar
  65. Holyoak, K. J., & Cheng, P. W. (2011). Causal learning and inference as a rational process: The new synthesis. Annual Review of Psychology, 62, 135–163. doi:10.1146/annurev.psych.121208.131634 PubMedGoogle Scholar
  66. Holyoak, K. J., Lee, H. S., & Lu, H. (2010). Analogical and category-based inference: A theoretical integration with Bayesian causal models. Journal of Experimental Psychology: General, 139, 702–727.Google Scholar
  67. Holyoak, K. J., & Thagard, P. (1989). Analogical mapping by constraint satisfaction. Cognitive Science, 13, 295–355.Google Scholar
  68. Howson, C., & Urbach, P. (1993). Scientific reasoning: The Bayesian approach. Chicago, IL: Open Court.Google Scholar
  69. Hull, C. (1943). Principles of behavior. New York, NY: Appleton-Century-Crofts.Google Scholar
  70. Hunt, E. B. (1962). Concept learning: An information processing problem. New York, NY: Wiley.Google Scholar
  71. Imai, M. (1995). Asymmetry in the taxonomic assumption: Word learning versus property induction. In E. V. Clark (Ed.), Proceedings of the 27th Annual Child Language Research Forum (pp. 157–167). Stanford, CA: Stanford University, Center for the Study of Language and Information.Google Scholar
  72. Inhelder, B., & Piaget, J. (1964). The early growth of logic in the child. London, UK: Routledge & Kegan Paul.Google Scholar
  73. Jern, A., & Kemp, C. (2013). A probabilistic account of exemplar and category generation. Cognitive Psychology, 66, 85–125.PubMedGoogle Scholar
  74. Keil, F. C. (1979). Semantic and conceptual development. Cambridge, MA: Harvard University Press.Google Scholar
  75. Kemp, C. (2011). Inductive reasoning about chimeric creatures. In J. Shawe-Taylor, R. Zemel, P. Bartlett, F. C. N. Pereira, & K. Q. Weinberger (Eds.), Advances in neural information processing systems 24 (pp. 316–324). Cambridge, MA: MIT Press.Google Scholar
  76. Kemp, C. (2012). Exploring the conceptual universe. Psychological Review, 119, 685–722.PubMedGoogle Scholar
  77. Kemp, C., Chang, K. K., & Lombardi, L. (2010a). Category and feature identification. Acta Psychologica, 133, 216–233.PubMedGoogle Scholar
  78. Kemp, C., Han, F., & Jern, A. (2011). Concept learning and modal reasoning. In L. Carlson, C. Hölscher, & T. F. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp. 513–518). Austin, TX: Cognitive Science Society.Google Scholar
  79. Kemp, C., & Jern, A. (2009). Abstraction and relational learning. In Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, & A. Culotta (Eds.), Advances in neural information processing systems 22 (pp. 934–942). Cambridge, MA: MIT Press.Google Scholar
  80. Kemp, C., Jern, A., & Xu, F. (2009). Individuation, identification and object discovery. In Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, & A. Culotta (Eds.), Advances in neural information processing systems 22 (pp. 925–933). Cambridge, MA: MIT Press.Google Scholar
  81. Kemp, C., Shafto, P., & Tenenbaum, J. B. (2012). An integrated account of generalization across objects and features. Cognitive Psychology, 1–2, 35–73.Google Scholar
  82. Kemp, C., & Tenenbaum, J. B. (2009). Structured statistical models of inductive reasoning. Psychological Review, 116, 20–58. doi:10.1037/a0014282 PubMedGoogle Scholar
  83. Kemp, C., Tenenbaum, J. B., Niyogi, S., & Griffiths, T. L. (2010b). A probabilistic model of theory formation. Cognition, 114, 165–196. doi:10.1016/j.cognition.2009.09.003 PubMedGoogle Scholar
  84. Lacouture, Y., & Marley, A. A. J. (1991). A connectionist model of choice and reaction time in absolute identification. Connection Science, 3, 401–433.Google Scholar
  85. Lambon Ralph, M. A., Graham, K. S., Ellis, A. W., & Hodges, J. R. (1998). Naming in semantic dementia—what matters? Neuropsychologia, 36, 775–784.PubMedGoogle Scholar
  86. Landy, D., & Goldstone, R. L. (2005). How we learn about things we don’t already understand. Journal of Experimental and Theoretical Artificial Intelligence, 17, 343–369.Google Scholar
  87. Langley, P., Simon, H. A., Bradshaw, G. L., & Zytkow, J. M. (1987). Scientific discovery: Computational explorations of the creative process. Cambridge, MA: MIT PRess.Google Scholar
  88. Leverington, D. (2003). Babylon to Voyager and beyond: A history of planetary astronomy. Cambridge, UK: University of Cambridge.Google Scholar
  89. Lombardi, L., & Sartori, G. (2007). Models of relevant cue integration in name retrieval. Journal of Memory and Language, 57, 101–125.Google Scholar
  90. López, A., Atran, S., Coley, J. D., Medin, D., & Smith, E. E. (1997). The tree of life: Universal and cultural features of folkbiological taxonomies and inductions. Cognitive Psychology, 32, 251–295.Google Scholar
  91. Love, B. C. (2002). Comparing supervised and unsupervised category learning. Psychonomic Bulletin & Review, 9, 829–835. doi:10.3758/BF03196342 Google Scholar
  92. Luce, R. D., Green, D. M., & Weber, D. L. (1976). Attention bands in absolute identification. Perception & Psychophysics, 20, 49–54. doi:10.3758/BF03198705 Google Scholar
  93. MacNamara, J. (1972). Cognitive basis of language learning in infants. Psychological Review, 79, 1–13. doi:10.1037/h0031901 PubMedGoogle Scholar
  94. Maratsos, M. (2001). How fast does a child learn a word? Behavioral and Brain Sciences, 24, 1111–1112.Google Scholar
  95. Markman, E. M. (1989). Categorization and naming in children: Problems of induction. Cambridge, MA: MIT Press.Google Scholar
  96. Markman, E. M. (1992). Constraints on word learning: Speculations about their nature, origins, and domain specificity. In M. R. Gunnar & M. Maratsos (Eds.), Modularity and constraints in language and cognition (pp. 59–101). Hillsdale, NJ: Erlbaum.Google Scholar
  97. Marr, D. (1982). Vision. San Francisco, CA: W. H. Freeman.Google Scholar
  98. Marzano, R. J., & Pickering, D. J. (2005). Building academic vocabulary: Teacher’s manual. Alexandria, VA: Association for Supervision and Curriculum Development.Google Scholar
  99. McCarrell, N. S., & Callanan, M. A. (1995). Form–function correspondences in children’s inference. Child Development, 66, 532–546.PubMedGoogle Scholar
  100. Medin, D. L., Coley, J. D., Storms, G., & Hayes, B. L. (2003). A relevance theory of induction. Psychonomic Bulletin & Review, 10, 517–532. doi:10.3758/BF03196515 Google Scholar
  101. Medin, D. L., Wattenmaker, W. D., & Hampson, S. E. (1987). Family resemblance, conceptual cohesiveness and category construction. Cognitive Psychology, 19, 242–279.PubMedGoogle Scholar
  102. Mendes, N., Rakoczy, H., & Call, J. (2008). Ape metaphysics: Object individuation without language. Cognition, 106, 730–749.PubMedGoogle Scholar
  103. Merriman, W. E., Schuster, J. M., & Hager, L. (1991). Are names ever mapped onto preexisting categories? Journal of Experimental Psychology: General, 120, 288–300.Google Scholar
  104. Mervis, C. B. (1987). Child-basic object categories and early lexical development. In U. Neisser (Ed.), Concepts and conceptual development (pp. 201–233). Cambridge, UK: Cambridge University Press.Google Scholar
  105. Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81–97.PubMedGoogle Scholar
  106. Murphy, G. L. (1993). Theories and concept formation. In I. Van Mechelen, J. Hampton, P. Theuns, & R. S. Michalski (Eds.), Categories and concepts: Theoretical views and inductive data analysis (pp. 173–200). London, UK: Academic Press.Google Scholar
  107. Murphy, G. L., & Ross, B. H. (2010). Category vs. object knowledge in category-based induction. Journal of Memory and Language, 63, 1–17.PubMedCentralPubMedGoogle Scholar
  108. Newell, A. (1989). Unified theories of cognition. Cambridge, MA: Harvard University Press.Google Scholar
  109. Nosofsky, R. M. (1986). Attention, similarity, and the identification-categorization relationship. Journal of Experimental Psychology: General, 115, 39–57.Google Scholar
  110. Nosofsky, R. M. (1988). On exemplar-based exemplar representations: Reply to Ennis (1988). Journal of Experimental Psychology: General, 117, 412–414.Google Scholar
  111. Nosofsky, R. M. (1992). Exemplar-based approach to relating categorization, identification and recognition. In F. G. Ashby (Ed.), Multidimensional models of perception and cognition (pp. 363–393). Hillsdale, NJ: Erlbaum.Google Scholar
  112. Osherson, D. N., Smith, E. E., Wilkie, O., Lopez, A., & Shafir, E. (1990). Category-based induction. Psychological Review, 97, 185–200.Google Scholar
  113. Pavlov, I. P. (1927). Conditioned reflexes: An investigation of the physiological activities of the cerebral cortex (G. V. Anrep, Trans.). London, UK: Oxford University Press.Google Scholar
  114. Pearl, J. (2000). Causality: Models, reasoning and inference. Cambridge, UK: Cambridge University Press.Google Scholar
  115. Peirce, C. S. (1957). The logic of abduction. In V. Tomas (Ed.), Peirce’s essays in the philosophy of science. New York, NY: Liberal Arts Press.Google Scholar
  116. Penn, D. C., Holyoak, K. J., & Povinelli, D. J. (2008). Darwin’s mistake: Explaining the discontinuity between human and nonhuman minds. Behavioral and Brain Sciences, 31, 109–129.PubMedGoogle Scholar
  117. Piaget, J., Montangero, J., & Billeter, J. (1977). La formation des correlats. In J. Piaget (Ed.), Recherches sur l’abstraction réfléchissante I (pp. 115–129). Paris, France: Presses Universitaires de France.Google Scholar
  118. Posner, M. I., & Keele, S. W. (1968). On the genesis of abstract ideas. Journal of Experimental Psychology, 77, 353–363.PubMedGoogle Scholar
  119. Pothos, E. M., & Chater, N. (2002). A simplicity principle in unsupervised human categorization. Cognitive Science, 26, 303–343.Google Scholar
  120. Pothos, E. M., Perlman, A., Bailey, T. M., Kurtz, K., Edwards, D. J., Hines, P., & McDonnell, J. V. (2011). Measuring category intuitiveness in unconstrained categorization tasks. Cognition, 121, 83–100. doi:10.1016/j.cognition.2011.06.002 PubMedGoogle Scholar
  121. Premack, D. (2010). Why humans are unique: Three theories. Perspectives on Psychological Science, 5, 22–32.Google Scholar
  122. Quine, W. V. O., & Ullian, J. (1978). The web of belief. New York, NY: Random House.Google Scholar
  123. Reber, A. S., & Reber, E. S. (2001). The Penguin dictionary of psychology. London, UK: Penguin.Google Scholar
  124. Rehder, B., & Burnett, R. (2005). Feature inference and the causal structure of categories. Cognitive Psychology, 50, 264–314.PubMedGoogle Scholar
  125. Rendell, L., & Seshu, R. (1990). Learning hard concepts through constructive induction: Framework and rationale. Computational Intelligence, 6, 247–270.Google Scholar
  126. Rips, L. J. (1975). Inductive judgments about natural categories. Journal of Verbal Learning and Verbal Behavior, 14, 665–681.Google Scholar
  127. Rips, L. J. (2010). Two causal theories of counterfactual conditionals. Cognitive Science, 34, 175–221. doi:10.1111/j.1551-6709.2009.01080.x PubMedGoogle Scholar
  128. Rogers, T. T., & McClelland, J. L. (2004). Semantic cognition: A parallel distributed processing approach. Cambridge, MA: MIT Press.Google Scholar
  129. Rumelhart, D. E., & Abrahamson, A. A. (1973). A model for analogical reasoning. Cognitive Psychology, 5, 1–28.Google Scholar
  130. Sartori, G., & Lombardi, L. (2004). Semantic relevance and semantic disorders. Journal of Cognitive Neuroscience, 16, 439–452.PubMedGoogle Scholar
  131. Saxe, R., Tenenbaum, J. B., & Carey, S. (2005). Secret agents: Inferences about hidden causes by 10- and 12-month-old infants. Psychological Science, 16, 995–1001.PubMedGoogle Scholar
  132. Schyns, P. G., Goldstone, R. L., & Thibaut, J.-P. (1998). The development of features in object concepts. Behavioral and Brain Sciences, 21, 1–17. doi:10.1017/S0140525X98520109 PubMedGoogle Scholar
  133. Shafto, P., Kemp, C., Bonawitz, E. B., Coley, J. D., & Tenenbaum, J. B. (2008). Inductive reasoning about causally transmitted properties. Cognition, 109, 175–192.PubMedGoogle Scholar
  134. Shafto, P., Kemp, C., Mansinghka, V., & Tenenbaum, J. B. (2011). A probabilistic model of cross-categorization. Cognition, 120, 1–25.PubMedGoogle Scholar
  135. Shepard, R. N. (1957). Stimulus and response generalization: A stochastic model relating generalization to distance in psychological space. Psychometrika, 22, 325–345.Google Scholar
  136. Shepard, R. N. (1986). Discrimination and generalization in identification and classification: Comment on Nosofsky. Journal of Experimental Psychology: General, 115, 58–61.Google Scholar
  137. Shepard, R. N. (1987). Towards a universal law of generalization for psychological science. Science, 237, 1317–1323. doi:10.1126/science.3629243 PubMedGoogle Scholar
  138. Sigala, N., Gabbiani, F., & Logothetis, N. K. (2002). Visual categorization and object representation in monkeys and humans. Journal of Cognitive Neuroscience, 14, 187–198.PubMedGoogle Scholar
  139. Skinner, B. F. (1938). The behavior of organisms: An experimental analysis. New York, NY: Appleton-Century.Google Scholar
  140. Skyrms, B. (1975). Choice and chance: An introduction to inductive logic. Belmont, CA: Dickenson.Google Scholar
  141. Sloman, S. A. (2005). Causal models: How people think about the world and its alternatives. Oxford: Oxford University Press.Google Scholar
  142. Sloman, S. A. (2007). Taxonomizing induction. In A. Feeney & E. Heit (Eds.), Inductive reasoning: Experimental, developmental and computational approaches (pp. 328–343). Cambridge, UK: Cambridge University Press.Google Scholar
  143. Sloman, S. A., & Lagnado, D. A. (2005). The problem of induction. In R. Morrison & K. Holyoak (Eds.), Cambridge handbook of thinking and reasoning (pp. 95–116). New York, NY: Cambridge University Press.Google Scholar
  144. Sloman, S. A., & Wisniewski, E. (1992). Extending the domain of a feature-based model of property induction. In J. K. Kruschke (Ed.), Proceedings of the 14th Annual Conference of the Cognitive Science Society (pp. 355–359). Hillsdale, NJ: Erlbaum.Google Scholar
  145. Sloutsky, V. M., & Fisher, A. V. (2002). The development of categorization. In B. H. Ross (Ed.), The psychology of learning and motivation (Vol. 54, pp. 142–166). New York, NY: Academic Press.Google Scholar
  146. Sloutsky, V. M., & Fisher, A. V. (2004). Induction and categorization in young children: A similarity based model. Journal of Experimental Psychology: General, 133, 166–188.Google Scholar
  147. Smith, E. E., Langston, C., & Nisbett, R. E. (1992). The case for rules in reasoning. Cognitive Science, 16, 1–40.Google Scholar
  148. Smith, L. B., & Heise, D. (1992). Perceptual similarity and conceptual structure. In B. Burns (Ed.), Percepts, concepts and categories. Amsterdam, The Netherlands: Elsevier.Google Scholar
  149. Smoke, K. L. (1935). The experimental approach to concept learning. Psychological Review, 42, 274–279.Google Scholar
  150. Snedeker, J., & Gleitman, L. (2004). Why it is hard to label our concepts. In D. G. Hall & S. R. Waxman (Eds.), Weaving a lexicon (pp. 257–293). Cambridge, MA: MIT Press.Google Scholar
  151. Spelke, E. S. (1990). Principles of object perception. Cognitive Science, 14, 29–56.Google Scholar
  152. Spelke, E. S., Kestenbaum, R., Simons, D. J., & Wein, D. (1995). Spatiotemporal continuity, smoothness of motion and object identity in infancy. British Journal of Developmental Psychology, 13, 113–142.Google Scholar
  153. Sternberg, R. J. (1986). Toward a unified theory of human reasoning. Intelligence, 10, 281–314.Google Scholar
  154. Sternberg, R. J., & Gardner, M. K. (1983). Unities in inductive reasoning. Journal of Experimental Psychology: General, 112, 80–116.Google Scholar
  155. Sternberg, R. J., & Nigro, G. (1980). Developmental patterns in the solution of verbal analogies. Child Development, 51, 27–38.Google Scholar
  156. Sweller, N., & Hayes, B. K. (2010). More than one kind of inference: Re-examining what’s learned in feature inference and classification. Quarterly Journal of Experimental Psychology, 63, 1568–1589. doi:10.1080/17470210903438547 Google Scholar
  157. Tare, M., & Gelman, S. A. (2010). Determining that a label is kind-referring: Factors that influence children’s and adults’ novel word extensions. Journal of Child Language, 37, 1007–1026.PubMedCentralPubMedGoogle Scholar
  158. Tenenbaum, J. B., & Griffiths, T. L. (2001). Generalization, similarity, and Bayesian inference. Behavioral and Brain Sciences, 24, 629–640. doi:10.1017/S0140525X01000061 PubMedGoogle Scholar
  159. Tenenbaum, J. B., Griffiths, T. L., & Kemp, C. (2006). Theory-based Bayesian models of inductive learning and reasoning. Trends in Cognitive Sciences, 10, 309–318.PubMedGoogle Scholar
  160. Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011). How to grow a mind: Statistics, structure, and abstraction. Science, 331, 1279–1285. doi:10.1126/science.1192788 PubMedGoogle Scholar
  161. Thagard, P. (2001). Induction. In R. A. Wilson & F. C. Keil (Eds.), The MIT encyclopedia of the cognitive sciences. Cambridge, MA: MIT Press.Google Scholar
  162. Tremoulet, P. D., Leslie, A. M., & Hall, D. G. (2000). Infant individuation and identification of objects. Cognitive Development, 15, 499–522.Google Scholar
  163. Valdés-Peréz, R. E., Żytkow, J. M., & Simon, H. A. (1993). Scientific model-building as search in matrix spaces. In R. Fikes & W. G. Lehnert (Eds.), Proceedings of the Eleventh National Conference on Artificial Intelligence (pp. 472–478). Cambridge, MA: MIT Press.Google Scholar
  164. Van de Walle, G. A., Carey, S., & Prevor, M. (2000). Bases for object individuation in infancy: Evidence from manual search. Journal of Cognition and Development, 1, 249–280.Google Scholar
  165. Vickers, J. (2012). The problem of induction. In E. N. Zalta (Ed.), Stanford encyclopedia of philosophy (Fall 2012 ed.). Stanford, CA: Stanford University, Metaphysics Research Lab.Google Scholar
  166. Werner, H., & Kaplan, E. (1952). The acquisition of word meanings: A developmental study. Monographs of the Society for Research in Child Development, 15, 1–119.Google Scholar
  167. Wisniewski, E. J., & Medin, D. L. (1994). On the interaction of theory and data in concept learning. Cognitive Science, 18, 221–281.Google Scholar
  168. Xu, F. (2005). Categories, kinds, and object individuation in infancy. In L. Gershkoff-Stowe & D. H. Rakison (Eds.), Building object categories in developmental time (pp. 63–89). Mahwah, NJ: Erlbaum.Google Scholar
  169. Xu, Y., & Kemp, C. (2010). Inference and communication in the game of Password. In J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R. Zemel, & A. Culotta (Eds.), Advances in neural information processing systems 23 (pp. 2514–2522). Cambridge, MA: MIT Press.Google Scholar
  170. Yamauchi, T., & Markman, A. B. (1998). Category learning by inference and classification. Journal of Memory and Language, 39, 124–148.Google Scholar

Copyright information

© Psychonomic Society, Inc. 2013

Authors and Affiliations

  1. 1.Department of PsychologyCarnegie Mellon UniversityPittsburghUSA

Personalised recommendations