Bayes nets (Pearl release_cvef2aim2jabnjrspvwxhwe73y

by Glymour Spirtes, Scheines Waldmann, Cheng, Hagmayer, Blaisdell

Released as a article-journal by Waldmann.



Theories of causal reasoning and learning often implicitly assume that the structural implications of causal models and empirical evidence are consistent. However, for probabilistic causal relations this may not be the case. Mismatches between structural implications and empirical evidence may lead to distortions of empirical evidence. Previous work has shown that people may use the generative causal relations A → B and B → C to infer a positive relation between events A and C, despite data showing that these events are actually independent (von Sydow et al., 2009, 2010). Here we used an economic trial-by-trial learning scenario to investigate how transitive reasoning in intransitive situations with even negatively related distal events may relate to betting behavior. Experiment 1 shows that transitive reasoning does affect not only probability estimates but betting as well. Experiment 2 shows that the effect remains stable even after repeated betting and feedback.
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