Optimal inference of sameness

Ronald Van Den Berg, Michael Vogel, Krešimir Josić, Wei Ji Ma

Research output: Contribution to journalArticlepeer-review

Abstract

Deciding whether a set of objects are the same or different is a cornerstone of perception and cognition. Surprisingly, no principled quantitative model of sameness judgment exists. We tested whether human sameness judgment under sensory noise can be modeled as a form of probabilistically optimal inference. An optimal observer would compare the reliability-weighted variance of the sensory measurements with a set size-dependent criterion. We conducted two experiments, in which we varied set size and individual stimulus reliabilities. We found that the optimal-observer model accurately describes human behavior, outperforms plausible alternatives in a rigorous model comparison, and accounts for three key findings in the animal cognition literature. Our results provide a normative footing for the study of sameness judgment and indicate that the notion of perception as nearoptimal inference extends to abstract relations.

Original languageEnglish (US)
Pages (from-to)3178-3183
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume109
Issue number8
DOIs
StatePublished - Feb 21 2012

Keywords

  • Bayesian inference
  • Decision making
  • Ideal observer
  • Vision

ASJC Scopus subject areas

  • General

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