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.
Neural dynamics for working memory and evidence integration during olfactory navigation in drosophila.bioRxiv, pages 2024–10, 2025
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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.