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  • Title: ➤  Context-specific Regulation Of Learning Rates In Continuous Choices
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  • Internet Archive ID: osf-registrations-qft2p-v1

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Participants will virtually go fishing for crabs around an island. Concretely, 60 times participants will see a boat take them to one of six locations around the island, where, each time, they will perform 10 trials before being taken to the next, randomly selected, location. On each trial, participants will position a cage hanging from the top of the screen along the screen's y-axis and drop it, trying to catch as many crabs as possible. As the cage is sinking, five crabs will crawl out of one location in the sand at the bottom of the screen and spread out a bit, each of which will either be caught by the cage or run away. Locations where crabs will crawl out of the sand will be randomly drawn from the normal sampling distribution. The mean of the sampling distribution will, in turn, be drawn from the normal prior distribution at the beginning of each block, the mean of which will be the centre of the screen. Correspondingly, participants will be told that, around this island, crabs live in groups which are denser near the centre, so that they should always try to find the centre of the group of crabs they are currently fishing for and drop their cages above it. On two adjacent locations around the island, the standard deviations of the prior distributions will be relatively high, while the standard deviations of the sampling distributions will be relatively low. On the two adjacent locations on the opposite side of the island, the standard deviations of the prior distributions will be relatively low, while the standard deviations of the sampling distributions will be relatively high. On the two locations in between, the standard deviations of both the prior and sampling distributions will be intermediate. As such, we expect participants to learn (1) that they should use a relatively high initial learning rate in the low sampling sigma environments, a relatively low initial learning rate in the high sampling sigma environments and an intermediate learning rate in the medium sampling sigma environments, and (2) that they should decrease their learning rates over the course of each block in all environments.

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"Context-specific Regulation Of Learning Rates In Continuous Choices" is available for download from The Internet Archive in "data" format, the size of the file-s is: 0.11 Mbs, and the file-s went public at Mon Dec 19 2022.

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  • Added Date: 2022-12-19 06:00:41
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