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  How do people learn how to plan?

Jain, Y., Gupta, S., Rakesh, V., Dayan, P., Callaway, F., & Lieder, F. (2019). How do people learn how to plan? In Conference on Cognitive Computational Neuroscience (CCN 2019) (pp. 826-829). doi:10.32470/CCN.2019.1313-0.

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CCN-2019-Jain.pdf (Any fulltext), 135KB
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 Creators:
Jain, YR, Author
Gupta, S, Author
Rakesh, V, Author
Dayan, P1, 2, Author           
Callaway, F, Author
Lieder, F, Author
Affiliations:
1Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_3017468              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: How does the brain learn how to plan? We reverse-engineer people's underlying learning mechanisms by combining rational process models of cognitive plasticity with recently developed empirical methods that allow us to trace the temporal evolution of people's planning strategies. We find that our Learned Value of Computation model (LVOC) accurately captures people's average learning curve. However, there were also substantial individual differences in metacognitive learning that are best understood in terms of multiple different learning mechanisms -- including strategy selection learning. Furthermore, we observed that LVOC could not fully capture people's ability to adaptively decide when to stop planning. We successfully extended the LVOC model to address these discrepancies. Our models broadly capture people's ability to improve their decision mechanisms and represent a significant step towards reverse-engineering how the brain learns increasingly more effective cognitive strategies through its interaction with the environment.

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 Dates: 2019-09
 Publication Status: Published online
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 Identifiers: DOI: 10.32470/CCN.2019.1313-0
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Title: Conference on Cognitive Computational Neuroscience (CCN 2019)
Place of Event: Berlin, Germany
Start-/End Date: 2019-09-13 - 2019-09-16

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Title: Conference on Cognitive Computational Neuroscience (CCN 2019)
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: PS-2A.70 Start / End Page: 826 - 829 Identifier: -