Bayesian Occam's Razor Is a Razor of the People

Thomas Blanchard, Tania Lombrozo, Shaun Nichols

Research output: Contribution to journalArticle

2 Citations (Scopus)

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 (BOR) 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.

Original languageEnglish (US)
Pages (from-to)1345-1359
Number of pages15
JournalCognitive Science
Volume42
Issue number4
DOIs
StatePublished - May 1 2018

Fingerprint

Prescriptions
Experiments

All Science Journal Classification (ASJC) codes

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Artificial Intelligence

Keywords

  • Bayesianism
  • Explanation
  • Flexibility
  • Probability
  • Simplicity

Cite this

Blanchard, Thomas ; Lombrozo, Tania ; Nichols, Shaun. / Bayesian Occam's Razor Is a Razor of the People. In: Cognitive Science. 2018 ; Vol. 42, No. 4. pp. 1345-1359.
@article{d6c3602bee2142cb9ffef03b68835806,
title = "Bayesian Occam's Razor Is a Razor of the People",
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 (BOR) 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",
author = "Thomas Blanchard and Tania Lombrozo and Shaun Nichols",
year = "2018",
month = "5",
day = "1",
doi = "10.1111/cogs.12573",
language = "English (US)",
volume = "42",
pages = "1345--1359",
journal = "Cognitive Science",
issn = "0364-0213",
publisher = "Wiley-Blackwell",
number = "4",

}

Bayesian Occam's Razor Is a Razor of the People. / Blanchard, Thomas; Lombrozo, Tania; Nichols, Shaun.

In: Cognitive Science, Vol. 42, No. 4, 01.05.2018, p. 1345-1359.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Bayesian Occam's Razor Is a Razor of the People

AU - Blanchard, Thomas

AU - Lombrozo, Tania

AU - Nichols, Shaun

PY - 2018/5/1

Y1 - 2018/5/1

N2 - 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 (BOR) 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.

AB - 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 (BOR) 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.

KW - Bayesianism

KW - Explanation

KW - Flexibility

KW - Probability

KW - Simplicity

UR - http://www.scopus.com/inward/record.url?scp=85034667657&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85034667657&partnerID=8YFLogxK

U2 - 10.1111/cogs.12573

DO - 10.1111/cogs.12573

M3 - Article

VL - 42

SP - 1345

EP - 1359

JO - Cognitive Science

JF - Cognitive Science

SN - 0364-0213

IS - 4

ER -