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Staying afloat on Neurath's boat - Heuristics for sequential causal learning

Bramley, N; Dayan, P; Lagnado, DA; (2015) Staying afloat on Neurath's boat - Heuristics for sequential causal learning. In: Noelle, DC and Dale, R and Warlaumont, AS and Yoshimi, J and Matlock, T and Jennings, CD and Maglio, PP, (eds.) Proceedings of Annual Meeting of the Cognitive Science Society (CogSci 2015): Mind, Technology, and Society. Cognitive Science Society: Pasadena, California, United States. Green open access

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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.

Type: Proceedings paper
Title: Staying afloat on Neurath's boat - Heuristics for sequential causal learning
Event: 37th Annual Meeting of the Cognitive Science Society (CogSci 2015): Mind, Technology, and Society
Open access status: An open access version is available from UCL Discovery
Publisher version: https://mindmodeling.org/cogsci2015/papers/0055/pa...
Language: English
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
URI: https://discovery.ucl.ac.uk/id/eprint/1501877
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