Causal thinking

Causality in the Sciences

Volumn , Issue , 2011, Pages

  Lagnado, David ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

Causal learning; Causal mental models; Interventions; Mental simulation; Reasoning

Indexed keywords

EID: 84920159730     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1093/acprof:oso/9780199574131.003.0007     Document Type: Chapter

References (75)

1. Ahn, W. & Kalish, C. (2000). The role of covariation vs. mechanism information in causal attribution. In R. Wilson, & F. Keil (eds.) Cognition and Explanation, Cambridge, MA: MIT Press.
2. Barsalou, L. (1999). Perceptual symbol systems. Behavioral and Brain Sciences, 22, 577-660.
3. Barsalou, L.W., Simmons, W. K., Barbey, A. K. & Wilson, C. D. (2003). Grounding conceptual knowledge in modality-specific systems. Trends in Cognitive Science., 7, 84-91.
4. Braine, M. & O'Brien, D. (1998). Mental Logic. Mahwah, NJ: Lawrence Erlbaum Associates.
5. Brass, M. & Heyes, C.M. (2005). Imitation: Is cognitive neuroscience solving the correspondence problem? Trends in Cognitive Science, 9, 489-495.
6. Bower, G.H. (1970). Organizational factors in memory. Cognitive Psychology, 1, 18-46.
7. Cartwright, N. (2007). Hunting Causes and Using Them: Approaches in Philosophy and Economics, Cambridge: Cambridge University Press.
8. Cheng, P.W. (1997). From covariation to causation: A causal power theory. Psychological Review, 104, 367-405.
9. Collingwood, R. (1940). An Essay on Metaphysics. Oxford: Clarendon Press.
10. Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24, 87-185.
11. Craik, K. (1952). The Nature of Explanation. Cambridge University Press, Cambridge, UK.
12. Einhorn, H. J. & Hogarth, R. M. (1986). Judging probable cause. Psychological Bulletin, 99, 3-19.
13. Evans, J. (2002). Logic and human reasoning: An assessment of the deduction paradigm. Psychological Bulletin, 128, 978-96.
14. Fernbach, P.M. & Sloman, S.A. (2009). Causal learning with local computations. Journal of Experimental Psychology: Learning, Memory, and Cognition. 35(3), 678-693.
15. Glymour, C. (2007). Statistical jokes and social effects: Intervention and invariance in causal relations. In Gopnik, A., & Schultz, L. (eds.), Causal learning: Psychology, Philosophy, and Computation, pp. 294-300. Oxford:Oxford University Press.
16. Goldvarg, Y. Johnson-Laird, P.N. (2001). Naïve causality: A mental model theory of causal meaning and reasoning. Cognitive Science, 25, 565-610.
17. Gopnik, A. & Schultz, L. (2007). Causal Learning: Psychology, Philosophy, and Computation. Oxford: Oxford University Press.
18. Gopnik, A., Glymour, C., Sobel, D. M., Schulz, L. E., Kushnir, T., & Danks, D. (2004). A theory of causal learning in children: Causal maps and Bayes nets. Psychological Review, 111, 1-31.
19. Griffiths, T.L. & Tenenbaum, J.B. (2005). Structure and strength in causal induction. Cognitive Psychology, 51, 334-384.
20. Grush, R. (2004). The emulation theory of representation: Motor control, imagery, and perception. Behavioral and Brain Sciences, 27, 377-396.
21. Hadamard, J. (1954). The Psychology of Invention in the Mathematical Field. New York: Dover.
22. Hagmayer, Y., & Waldmann, M.R. (2000). Simulating causal models: The way to structural sensitivity. In L. Gleitman & A. Joshi (Eds.), Proceedings of the Twenty-second Annual Conference of the Cognitive Science Society. Mahwah, NJ: Erlbaum.
23. Hall, G. (2002). Associative structures in Pavlovian and instrumental conditioning. In C.R. Gallistel (ed.), Stevens' Handbook of Experimental Psychology, 3rd edition, Vol. 3, pp. 1-45. New York: John Wiley.
24. Hastie, R. & Pennington, N. (2000). Explanation-based decision making. In T. Connolly, H. R. Arkes and K. R. Hammond (eds): Judgment and Decision Making: An Interdisciplinary Reader (2nd ed.). pp. 212-28. Cambridge University Press.
25. Halford, G.S., Cowan, N., & Andrews, G. (2007). Separating cognitive capacity from knowledge: A new hypothesis. Trends in Cognitive Sciences, 11 (6), 236-242.
26. Hegarty, M. (2004). Mechanical reasoning as mental simulation. Trends in Cognitive Science, 8, 280-285.
27. Hegarty, M. (1992). Mental animation: Inferring motion from static diagrams of mechanical systems. Journal of Experimental Psychology: Learning, Memory and Cognition, 18, 1084-1102.
28. Heller, K. J. (2006). The cognitive psychology of circumstantial evidence. Michigan Law Review, 105, 241-305.
29. Inhelder, B. and Piaget, J. (1958). The Growth of Logical Thinking from Childhood to Adolescence. New York: Basic Books.
30. Jeannerod, M. (2006). Motor Cognition: What Actions Tell the Self. Oxford:Oxford University Press.
31. Johnson-Laird, P.N. (1983). Mental Models. Cambridge: Cambridge University Press.
32. Johnson-Laird, P.N. (2006). How We Reason. Oxford: Oxford University Press.
33. Kahneman, D. & Tversky, A. (1982). The simulation heuristic. In D. Kahneman, P. Slovic & A. Tversky (eds.), Judgment under Uncertainty:Heuristics and Biases (pp. 201-208). New York: Cambridge University Press.
34. Krynski, T.R. & Tenenbaum, J.B. (2007). The role of causality in judgment under uncertainty. Journal of Experimental Psychology: General, 136, 430-450.
35. Lagnado, D.A. (2009). A causal framework for learning and reasoning. Behavioral and Brain Sciences, 32, (2), 211-212.
36. Lagnado, D.A. (2010). Thinking about evidence. To appear in Dawid, P, Twining, W., Vasilaki, M. eds. Evidence, Inference and Enquiry. British Academy/OUP. (In Press).
37. Lagnado, D.A. & Sloman, S.A. (2004). The advantage of timely intervention. Journal of Experimental Psychology: Learning, Memory & Cognition, 30, 856-876.
38. Lagnado, D.A. & Sloman, S.A. (2002). Learning causal structure. In W. Gray & C. D. Schunn (Eds.), Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society, Erlbaum.
39. Lagnado, D.A., Waldmann, M.R., Hagmayer, Y., & Sloman, S.A. (2007). Beyond covariation: Cues to causal structure. In Gopnik, A., & Schultz, L. (eds.), Causal learning: Psychology, Philosophy, and Computation, pp. 154-172. Oxford: Oxford University Press.
40. Lagnado, D.A. & Harvey, N. (2008). The impact of discredited evidence. Psychonomic Bulletin and Review, 15, 1166-1173.
41. Lagnado, D.A. & Sloman, S. A. (2006). Time as a guide to cause. Journal of Experimental Psychology: Learning, Memory & Cognition, 32, 451-460.
42. Lagnado, D. A. & Loventoft-Jessen, J. (in prep.). Learning causal models through multiple interventions.
43. Meder, B., Hagmayer, Y., & Waldmann, M. R. (2008). Inferring interventional predictions from observational learning data. Psychonomic Bulletin & Review, 15, 75-80.
44. Michotte, A. (1954/1963). The Perception of Causality. London: Methuen.
45. 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.
46. Nersessian, N. J. (2008). Creating Scientific Concepts. Cambridge, MA: MIT Press.
47. Oaksford, M. & Chater, N. (2007). Bayesian Rationality: The Probabilistic Approach to Human Reasoning. Oxford: Oxford University Press.
48. Pearl, J. (2000). Causality. Cambridge: Cambridge University Press.
49. Rips, L. J. (1983). Cognitive processes in prepositional reasoning. Psychological Review, 90, 38-71.
50. Shanks, D. R. (2004). Judging covariation and causation. In D. Koehler & N. Harvey (Eds.), Blackwell Handbook of Judgment and Decision Making. Oxford:Blackwell.
51. Shanks, D. R. (1995). The Psychology of Associative Learning. Cambridge:Cambridge University Press.
52. Schlottmann, A. (2001). Perception versus knowledge of cause-and-effect in children: When seeing is believing. Current Directions in Psychological Science, 10, 111-115.
53. Scholl, B. J. (2005). Innateness and (Bayesian) visual perception: Reconciling nativism and development. In P. Carruthers, S. Laurence, & S. Stich (Eds.), The Innate Mind: Structure and Contents pp. 34-52. Oxford: Oxford University Press.
54. Schwartz, D.L. (1999). Physical imagery: Kinematic vs. dynamic models. Cognitive Psychology. 38, 433-464.
55. Schwartz, D.L. & Black, T. (1999). Inferences through imagined actions:Knowing by simulated doing. Journal of Experimental Psychology: Learning, Memory & Cognition, 25, 116-136.
56. Shanks, D. R. & Dickinson, A. (1987). Associative accounts of causality judgment. In G. H. Bower (Ed.), The Psychology of Learning and Motivation:Advances in Research and Theory Vol. 21, pp. 229-261. San Diego, CA:Academic Press.
57. Sloman, S. A. (2005). Causal Models; How People Think About the World and its Alternatives. New York: Oxford University Press.
58. Sloman, S. A., Barbey, A. K. & Hotaling, J. (2009). A causal model theory of the meaning of cause, enable, and prevent. Cognitive Science, 33, 21-50.
59. Sloman, S. A. & Lagnado, D. A. (2005). Do we do? Cognitive Science,. 29, 5-39.
60. Spirtes, P., Glymour, C., & Schienes, R. (1993). Causation, Prediction, and Search. New York: Springer-Verlag.
61. Steel, D. (2008). Across the Boundaries: Extrapolation in Biology and Social Science. New York: Oxford University Press.
62. Steyvers, M., Tenenbaum, J. B., Wagenmakers, E. J., & Blum, B. (2003). Inferring causal networks from observations and interventions. Cognitive Science, 27, 453-489.
63. Suppes, P. (1970). A Probabilistic Theory of Causality. Amsterdam: North-Holland.
64. Tenenbaum, J.B., & Griffiths, T.L. (2003). Theory-based causal inference. Advances in Neural Information Processing Systems 15, pp. 35-42. Cambridge, MA: MIT Press.
65. Tolman, E. C. (1948). Cognitive maps in rats and men. Psychological Review, 55, 189-208.
66. Wagemans, J., van Lier, R. & Scholl, B.J. (2006). Introduction to Michotte's heritage in perception and cognition research. Acta Psychologica, 123, 1-19.
67. Waldmann, M.R. (1996). Knowledge-based causal induction. In D. R. Shanks, K. J. Holyoak, & D. L. Medin (Eds.), The Psychology of Learning and Motivation Vol. 34, pp. 47-88. San Diego, CA: Academic Press.
68. Waldmann, M.R. & Holyoak, K.J. (1992). Predictive and diagnostic learning within causal models: Asymmetries in cue competition. Journal of Experimental Psychology, General, 121(2), 222-236.
69. Waldmann, M.R., & Hagmayer, Y. (2005). Seeing versus doing: Two modes of accessing causal knowledge. Journal of Experimental Psychology: Learning, Motivation, and Cognition, 31, 216-227.
70. Waldmann, M.R., Hagmayer, Y, & Blaisdell, A.P. (2006). Beyond the information given: Causal models in learning and reasoning. Current Directions in Psychological Science, 15 (6), 307-311.
71. Wason, P.C. (1983). Realism and rationality in the selection task. In J. St. B. T. Evans (ed.), Thinking and Reasoning: Psychological Approaches. London:Routledge & Kegan.
72. Williamson, J. (2005). Bayesian Nets and Causality: Philosophical and Computational Foundations. Oxford: Oxford University Press.
73. Wolff, P. (2007). Representing causation. Journal of Experimental Psychology:General, 136, 82-111.
74. Wolpert, D.M. (2007). Probabilistic models in human sensorimotor control. Human Movement Science, 26, 511-524.
75. Woodward, J. (2003). Making Things Happen. A Theory of Causal Explanation. Oxford: Oxford University Press.