Hypothesis space checking in intuitive reasoning

Abstract

The process of generating a new hypothesis often begins with the recognition that all of the hypotheses currently under consideration are wrong. While this sort of falsification is straightforward when the observations are incompatible with each of the hypotheses, an interesting situation arises when the observations are implausible under the hypotheses but not incompatible with them. We propose a formal account, inspired by statistical model checking, as an explanation for how people reason about these probabilistic falsifications. We contrast this account with approaches such as Bayesian inference that account for hypothesis comparison but do not explain how a reasoner might decide that the hypothesis space needs to be expanded.


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