Heuristics in Covariation-based Induction of Causal Models: Sufficiency and Necessity Priors

Expanding the Space of Cognitive Science - Proceedings of the 33rd Annual Meeting of the Cognitive Science Society, CogSci 2011

Volumn , Issue , 2011, Pages 3110-3115

  Mayrhofer, Ralf ^a   Waldmann, Michael R ^a  

^a UNIVERSITY OF GÖTTINGEN   (Germany)

Author keywords

causal Bayes nets; causal induction; heuristics

Indexed keywords

BAYES NET; BOTTOM-UP AND TOP-DOWN; CAUSAL BAYE NET; CAUSAL INDUCTION; CAUSAL MODELING; CO-VARIATIONS; HEURISTIC; LEARNING THEORY; TEMPORAL ORDERING; TOP-DOWN LEARNING;

EID: 83555166443     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Fernbach, P. M., & Sloman, S. A. (2009). Causal learning with local computations. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35, 678-693.
2. Goldvarg, E., & Johnson-Laird, P. N. (2001). Naïve causality: a mental model theory of causal meaning and reasoning. Cognitive Science, 25, 565-610.
3. 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, 3-32.
4. Griffiths, T. L., & Tenenbaum, J. B. (2009). Theory-based causal induction. Psychological Review, 116, 661-716.
5. Hume, D. (1748/1977). An enquiry concerning human understanding. Indianapolis: Hackett Publishing Company.
6. Lagnado, D. A., Waldmann, M. A., Hagmayer, Y., & Sloman, S. A. (2007). Beyond covariation. Cues to causal structure. In A. Gopnik & L. E. Schulz (Eds.), Causal learning: Psychology, philosophy, and computation (pp. 154-172). Oxford: Oxford University Press.
7. Lu, H., Yuille, A. L., Liljeholm, M., Cheng, P. W., & Holyoak, K. J. (2008). Bayesian generic priors for causal learning. Psychological Review, 115, 955-982.
8. Mayrhofer, R., Hagmayer, Y., & Waldmann, M. R. (2010). Agents and causes: A Bayesian error attribution model of causal reasoning. Proceedings of the Thirty-Second Annual Conference of the Cognitive Science Society.
9. Pearl, J. (2000). Causality: Models, reasoning, and inference. Cambridge, MA: Cambridge University Press.
10. Pearl, J. (2000). Causality. Cambridge: Cambridge University Press.
11. Schulz, L. E., & Sommerville, J. (2006). God does not play dice: Causal determinism and preschoolers’ causal inferences. Child Development, 77, 427-442.
12. Spirtes, P., Glymour, C., & Scheines, P. (1993). Causation, prediction, and search. New York: Springer.
13. Steyvers, M., Tenenbaum, J. B., Wagenmakers, E-J., & Blum, B. (2003). Inferring causal networks from observations and interventions. Cognitive Science, 27, 453-489.
14. 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: Causal learning (pp. 47-88). San Diego: Academic Press.
15. Waldmann, M. R., & Hagmayer, Y. (in press). Causal reasoning. In D. Reisberg (Ed.), Oxford Handbook of Cognitive Psychology.