Behavioral and Brain Sciences 32 (2):211-212 (2009)
AbstractCan the phenomena of associative learning be replaced wholesale by a propositional reasoning system? Mitchell et al. make a strong case against an automatic, unconscious, and encapsulated associative system. However, their propositional account fails to distinguish inferences based on actions from those based on observation. Causal Bayes networks remedy this shortcoming, and also provide an overarching framework for both learning and reasoning. On this account, causal representations are primary, but associative learning processes are not excluded a priori
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References found in this work
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Causal Reasoning Through Intervention.York Hagmayer, Steven A. Sloman, David A. Lagnado & Michael R. Waldmann - 2007 - In Alison Gopnik & Laura Schulz (eds.), Causal Learning: Psychology, Philosophy, and Computation. Oxford University Press.
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