David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
Learn more about PhilPapers
Oxford University Press (2007)
Understanding causal structure is a central task of human cognition. Causal learning underpins the development of our concepts and categories, our intuitive theories, and our capacities for planning, imagination and inference. During the last few years, there has been an interdisciplinary revolution in our understanding of learning and reasoning: Researchers in philosophy, psychology, and computation have discovered new mechanisms for learning the causal structure of the world. This new work provides a rigorous, formal basis for theory theories of concepts and cognitive development, and moreover, the causal learning mechanisms it has uncovered go dramatically beyond the traditional mechanisms of both nativist theories, such as modularity theories, and empiricist ones, such as association or connectionism
|Keywords||Learning, Psychology of Causation|
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|Call number||BF318.C38 2007|
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York Hagmayer, Steven A. Sloman, David A. Lagnado & Michael R. Waldmann, Causal Reasoning Through Intervention.
Thomas Richardson, Laura Schulz & Alison Gopnik, Data-Mining Probabilists or Experimental Determinists.
Laura Schulz, Tamar Kushnir & Alison Gopnik, Learning From Doing: Intervention and Causal Inference.
Joshua B. Tenenbaum, Thomas L. Griffiths & Sourabh Niyogi, Intuitive Theories as Grammars for Causal Inference.
Henry M. Wellman & David Liu, Causal Reasoning as Informed by the Early Development of Explanations.
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Citations of this work BETA
Phyllis McKay Illari (2011). Mechanistic Evidence: Disambiguating the Russo–Williamson Thesis. International Studies in the Philosophy of Science 25 (2):139 - 157.
Nicolas J. Bullot (2014). Explaining Person Identification: An Inquiry Into the Tracking of Human Agents. Topics in Cognitive Science 6 (4):567-584.
York Hagmayer (2016). Causal Bayes Nets as Psychological Theories of Causal Reasoning: Evidence From Psychological Research. Synthese 193 (4):1107-1126.
Thomas L. Griffiths, David M. Sobel, Joshua B. Tenenbaum & Alison Gopnik (2011). Bayes and Blickets: Effects of Knowledge on Causal Induction in Children and Adults. Cognitive Science 35 (8):1407-1455.
Deena S. Weisberg & Alison Gopnik (2013). Pretense, Counterfactuals, and Bayesian Causal Models: Why What Is Not Real Really Matters. Cognitive Science 37 (7):1368-1381.
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