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.
Walking drosophila navigate complex plumes using stochastic decisions bi- ased by the timing of odor encounters.Elife, 9:e57524
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.bio-ph 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.