Inferring Intentional Agents From Violation of Randomness

Yuan Meng, Thomas L. Griffiths, Fei Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Humans have a strong “cognitive compulsion” to infer intentional agents from violation of randomness and such an agency-nonrandomness link emerges early in development. In two studies, we directly quantified, formalized, and compared both ends of this link for the first time. In Experiment 1, two groups of participants viewed the same 256 binary sequences (e.g., AABAAABA) and classified each as generated by agents/non-agents or by nonrandom/random processes. We found a strong correlation between two judgments: sequences viewed as more agentive also tended to be judged as less random. In Experiment 2, another two groups were asked to produce sequences that others might appreciate as agentive or nonrandom. Participant-generated sequences in the two conditions had a substantial overlap, indicating common guiding principles of agency and nonrandomness generation. Taken together, the present studies provide evidence for a shared cognitive basis of agency detection and subjective randomness.

Original languageEnglish (US)
Title of host publicationCogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society
Subtitle of host publicationComputational Foundations of Cognition
PublisherThe Cognitive Science Society
Pages2699-2704
Number of pages6
ISBN (Electronic)9780991196760
StatePublished - 2017
Externally publishedYes
Event39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017 - London, United Kingdom
Duration: Jul 26 2017Jul 29 2017

Publication series

NameCogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition

Conference

Conference39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017
Country/TerritoryUnited Kingdom
CityLondon
Period7/26/177/29/17

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

Keywords

  • agency
  • agency-nonrandomness link
  • animate-inanimate distinction
  • subjective randomness

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