  Soaring birds gain energy from stable ascending currents or shear. However,
it remains unclear whether energy loss due to drag can be overcome by
extracting work from transient turbulent fluctuations. We designed numerical
simulations of gliders navigating in a kinematic model that captures the
spatio-temporal correlations of atmospheric turbulence. Energy extraction is
enabled by an adaptive algorithm based on Monte Carlo tree search that
dynamically filters acquired information about the flow to plan future paths.
We show that net energy gain is feasible under realistic constraints. Glider
paths reflect patterns of foraging, where exploration of the flow is
interspersed with bouts of energy extraction through localized spirals.
