title: How do people learn from negative evidence? Non-monotonic generalizations and sampling assumptions in inductive reasoning.
abstract: A robust finding in category-based induction tasks is for positive observations to raise the willingness to generalize to other categories while negative observations lower the willingness to generalize. This pattern is referred to as monotonic generalization. Across three experiments we find systematic non-monotonicity effects, in which negative observations raise the willingness to generalize. Experiments 1 and 2 show that this effect emerges in hierarchically structured domains when a negative observation from a different category is added to a positive observation. They also demonstrate that this is related to a specific kind of shift in the reasoner's hypothesis space. Experiment 3 shows that the effect depends on the assumptions that the reasoner makes about how inductive arguments are constructed. Non-monotonic reasoning occurs when people believe the facts were put together by a helpful communicator, but monotonicity is restored when they believe the observations were sampled randomly from the environment.
authors.affiliation: Department of Psychology, University of Leuven, Belgium. Electronic address: wouter.voorspoels@ppw.kuleuven.be.
authors.forename: Wouter
authors.initials: W
authors.lastname: Voorspoels
authors.affiliation: School of Psychology, University of Adelaide, Australia. Electronic address: daniel.navarro@adelaide.edu.au.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Navarro
authors.affiliation: School of Psychology, University of Adelaide, Australia. Electronic address: amy.perfors@adelaide.edu.au.
authors.forename: Amy
authors.initials: A
authors.lastname: Perfors
authors.affiliation: School of Psychology, University of Adelaide, Australia. Electronic address: keith.ransom@adelaide.edu.au.
authors.forename: Keith
authors.initials: K
authors.lastname: Ransom
authors.affiliation: Department of Psychology, University of Leuven, Belgium. Electronic address: gert.storms@ppw.kuleuven.be.
authors.forename: Gert
authors.initials: G
authors.lastname: Storms
mesh_terms: D001499:Bayes Theorem; D003210:Concept Formation; D005793:Generalization, Psychological; D006801:Humans; D007858:Learning; D013850:Thinking
keywords: Bayesian inference; Inductive reasoning; Negative evidence; Relevance; Sampling assumptions