Bayes and Blickets: Effects of Knowledge on Causal Induction in Children and Adults
Article first published online: 4 OCT 2011
Copyright © 2011 Cognitive Science Society, Inc.
Volume 35, Issue 8, pages 1407–1455, November/December 2011
How to Cite
Griffiths, T. L., Sobel, D. M., Tenenbaum, J. B. and Gopnik, A. (2011), Bayes and Blickets: Effects of Knowledge on Causal Induction in Children and Adults. Cognitive Science, 35: 1407–1455. doi: 10.1111/j.1551-6709.2011.01203.x
- Issue published online: 2 NOV 2011
- Article first published online: 4 OCT 2011
- Received 23 June 2010; received in revised form 7 February 2011; accepted 8 February 2011
- Causal induction;
- Bayesian inference;
- Cognitive development;
- Knowledge effects
People are adept at inferring novel causal relations, even from only a few observations. Prior knowledge about the probability of encountering causal relations of various types and the nature of the mechanisms relating causes and effects plays a crucial role in these inferences. We test a formal account of how this knowledge can be used and acquired, based on analyzing causal induction as Bayesian inference. Five studies explored the predictions of this account with adults and 4-year-olds, using tasks in which participants learned about the causal properties of a set of objects. The studies varied the two factors that our Bayesian approach predicted should be relevant to causal induction: the prior probability with which causal relations exist, and the assumption of a deterministic or a probabilistic relation between cause and effect. Adults’ judgments (Experiments 1, 2, and 4) were in close correspondence with the quantitative predictions of the model, and children’s judgments (Experiments 3 and 5) agreed qualitatively with this account.