Staying afloat on Neurath’s boat: Heuristics for sequential causal learning

Neil Bramley, Peter Dayan, D.A. Lagnado

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

Abstract

Causal models are key to flexible and efficient exploitation of the environment. However, learning causal structure is hard, with massive spaces of possible models, hard-to-compute marginals and the need to integrate diverse evidence over many instances. We report on two experiments in which participants learnt about probabilistic causal systems involving three and four variables from sequences of interventions. Participants were broadly successful, albeit exhibiting sequential dependence and floundering under high background noise. We capture their behavior with a simple model, based on the "Neurath's ship'' metaphor for scientific progress, that neither maintains a probability distribution, nor computes exact likelihoods.
Original languageEnglish
Title of host publicationProceedings of the 37th Annual Meeting of the Cognitive Science Society
EditorsD. C. Noelle, R. Dale, A.S. Warlaumont, J. Yoshimi, T. Matlock, C.D. Jennings, P.P. Maglio
Place of PublicationAustin, TX
PublisherCognitive Science Society
Pages262-267
ISBN (Print)9780991196722
Publication statusPublished - 2015
Event37th Annual Meeting of the Cognitive Science Society - Pasadena, California, United States
Duration: 22 Jul 201525 Jul 2015
https://mindmodeling.org/cogsci2015/

Conference

Conference37th Annual Meeting of the Cognitive Science Society
Abbreviated titleCogSci2015
CountryUnited States
CityPasadena, California
Period22/07/1525/07/15
Internet address

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