Cognitive Science 42 (4):1345-1359 (2018)

Authors
Thomas Blanchard
University of Cologne
Abstract
Occam's razor—the idea that all else being equal, we should pick the simpler hypothesis—plays a prominent role in ordinary and scientific inference. But why are simpler hypotheses better? One attractive hypothesis known as Bayesian Occam's razor is that more complex hypotheses tend to be more flexible—they can accommodate a wider range of possible data—and that flexibility is automatically penalized by Bayesian inference. In two experiments, we provide evidence that people's intuitive probabilistic and explanatory judgments follow the prescriptions of BOR. In particular, people's judgments are consistent with the two most distinctive characteristics of BOR: They penalize hypotheses as a function not only of their numbers of free parameters but also as a function of the size of the parameter space, and they penalize those hypotheses even when their parameters can be “tuned” to fit the data better than comparatively simpler hypotheses.
Keywords Bayesianism  Explanation  Flexibility  Probability  Simplicity
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DOI 10.1111/cogs.12573
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References found in this work BETA

Bayesianism and Inference to the Best Explanation.Leah Henderson - 2014 - British Journal for the Philosophy of Science 65 (4):687-715.

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Epistemic Infrastructure for a Scientific Metaphysics.Amanda Bryant - 2021 - Grazer Philosophische Studien 98 (1):27-49.
Becoming Cognitive Science.Robert L. Goldstone - 2019 - Topics in Cognitive Science 11 (4):902-913.

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