David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
How ought we learn causal relationships? While Popper advocated a hypothetico-deductive logic of causal discovery, inductive accounts are currently in vogue. Many inductive approaches depend on the causal Markov condition as a fundamental assumption. This condition, I maintain, is not universally valid, though it is justifiable as a default assumption. In which case the results of the inductive causal learning procedure must be tested before they can be accepted. This yields a synthesis of the hypothetico-deductive and inductive accounts, which forms the focus of this paper. I discuss the justification of this synthesis and draw an analogy between objective Bayesianism and the account of causal learning presented here.
|Keywords||No keywords specified (fix it)|
No categories specified
(categorize this paper)
|Through your library||Only published papers are available at libraries|
Similar books and articles
L. Andrew Coward & Ron Sun (2004). Criteria for an Effective Theory of Consciousness and Some Preliminary Attempts. Consciousness and Cognition 13 (2):268-301.
Soshichi Uchii (1972). Inductive Logic with Causal Modalities: A Probabilistic Approach. Philosophy of Science 39 (2):162-178.
Alison Gopnik, Clark Glymour, David M. Sobel, Laura Schulz, Tamar Kushnir & David Danks, A Theory of Causal Learning in Children: Causal Maps and Bayes Nets.
Peter Spirtes (2011). Intervention, Determinism, and the Causal Minimality Condition. Synthese 182 (3):335-347.
Alison Gopnik, Clark Glymour, David M. Sobel & Laura E. Schultz, Causal Learning in Children: Causal Maps and Bayes Nets.
Charles Kemp, Noah D. Goodman & Joshua B. Tenenbaum (2010). Learning to Learn Causal Models. Cognitive Science 34 (7):1185-1243.
Added to index2009-01-28
Total downloads10 ( #118,353 of 1,008,193 )
Recent downloads (6 months)1 ( #64,735 of 1,008,193 )
How can I increase my downloads?