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  Active Function Learning

Jones, A., Schulz, E., Meder, B., & Ruggeri, A. (2019). Active Function Learning. In 40th Annual Cognitive Science Society Meeting (CogSci 2018): Changing / Minds (pp. 578-583). Red Hook, NY, USA: Curran.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0006-B389-5 Version Permalink: https://hdl.handle.net/21.11116/0000-0006-B3E0-2
Genre: Conference Paper

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https://cogsci.mindmodeling.org/2018/papers/0125/0125.pdf (Publisher version)
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 Creators:
Jones, A, Author
Schulz, E1, Author           
Meder, B, Author
Ruggeri, A, Author
Affiliations:
1External Organizations, ou_persistent22              

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 Abstract: How do people actively explore to learn about functional relationships, that is, how continuous inputs map onto continuous outputs? We introduce a novel paradigm to investigate information search in continuous, multi-feature function learning scenarios. Participants either actively selected or passively observed information to learn about an underlying linear function. We develop and compare different variants of rule-based (linear regression) and non-parametric (Gaussian process regression) active learning approaches to model participants' active learning behavior. Our results show that participants' performance is best described by a rule-based model that attempts to efficiently learn linear functions with a focus on high and uncertain outcomes. These results advance our understanding of how people actively search for information to learn about functional relations in the environment.

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 Dates: 2018-072019-01
 Publication Status: Issued
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Title: 40th Annual Cognitive Science Society Meeting (CogSci 2018)
Place of Event: Madison, WI, USA
Start-/End Date: 2018-07-25 - 2018-07-28

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Title: 40th Annual Cognitive Science Society Meeting (CogSci 2018): Changing / Minds
Source Genre: Proceedings
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Publ. Info: Red Hook, NY, USA : Curran
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 578 - 583 Identifier: ISBN: 978-1-5108-7205-9