Data for: Foraging decisions as multi-armed bandit problems: applying reinforcement learning algorithms to foraging data

Published: 8 Feb 2019 | Version 1 | DOI: 10.17632/t67pmwmsfw.1
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Description of this data

Data for the manuscript "Foraging decisions as multi-armed bandit problems: applying reinforcement learning algorithms to foraging data". This is an excel file with 4 tabs, each containing the data set for a group size (i.e., 10, 25, 50, and 100 larvae).

Experiment data files

This data is associated with the following publication:

Foraging decisions as multi-armed bandit problems: Applying reinforcement learning algorithms to foraging data

Published in: Journal of Theoretical Biology

Latest version

  • Version 1

    2019-02-08

    Published: 2019-02-08

    DOI: 10.17632/t67pmwmsfw.1

    Cite this dataset

    Morimoto, Juliano (2019), “Data for: Foraging decisions as multi-armed bandit problems: applying reinforcement learning algorithms to foraging data”, Mendeley Data, v1 http://dx.doi.org/10.17632/t67pmwmsfw.1

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Categories

Behavioral Ecology

Licence

CC BY NC 3.0 Learn more

The files associated with this dataset are licensed under a Attribution-NonCommercial 3.0 Unported licence.

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You are free to adapt, copy or redistribute the material, providing you attribute appropriately and do not use the material for commercial purposes.

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