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Adaptive planning in human search

Moritz J. F. Krusche, Eric Schulz, Arthur Guez, Maarten Speekenbrink
doi: https://doi.org/10.1101/268938
Moritz J. F. Krusche
1Warwick Business School, University of Warwick, Coventry, UK
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Eric Schulz
2Department of Psychology, Harvard University, Cambridge, Massachusetts, USA
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Arthur Guez
3Gatsby Computational Neuroscience Unit, University College London, London, UK
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Maarten Speekenbrink
4Department of Experimental Psychology, University College London, London, UK
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Abstract

How do people plan ahead when searching for rewards? We investigate planning in a foraging task in which participants search for rewards on an infinite two-dimensional grid. Our results show that their search is best-described by a model which searches at least 3 steps ahead. Furthermore, participants do not seem to update their beliefs during planning, but rather treat their initial beliefs as given, a strategy similar to a heuristic called root-sampling. This planning algorithm corresponds well with participants’ behavior in test problems with restricted movement and varying degrees of information, outperforming more complex models. These results enrich our understanding of adaptive planning in complex environments.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted May 14, 2018.
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Adaptive planning in human search
Moritz J. F. Krusche, Eric Schulz, Arthur Guez, Maarten Speekenbrink
bioRxiv 268938; doi: https://doi.org/10.1101/268938
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Adaptive planning in human search
Moritz J. F. Krusche, Eric Schulz, Arthur Guez, Maarten Speekenbrink
bioRxiv 268938; doi: https://doi.org/10.1101/268938

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