A tabular Q-learning agent with clock-state memory learns surging, casting, and downwind return to recover odor plumes in turbulent flows from direct numerical simulations.
Olfactory search at high Reynolds number.Proceedings of the na- tional academy of sciences, 99(20):12589–12593
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Clock-state olfactory search in turbulent flows using Q-learning: The geometry of plume recovery
A tabular Q-learning agent with clock-state memory learns surging, casting, and downwind return to recover odor plumes in turbulent flows from direct numerical simulations.