1 research outputs found
Adaptive planning in human search
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