Adaptive planning in human search
- Moritz Krusche, Warwick Business School, University of Warwick, Coventry, United Kingdom
- Eric Schulz, Harvard University, Cambridge, Massachusetts, United States
- Arthur Guez, Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom
- Maarten Speekenbrink, Department of Experimental Psychology, University College London, London, United Kingdom
AbstractHow 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 corre- sponds well with participants’ behavior in test problems with restricted movement and varying degrees of information, out- performing more complex models. These results enrich our understanding of adaptive planning in complex environments.
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