A deep reinforcement learning model that allows AI agents to track odor plumes
Feb 2023, phys.org
Insects track odor plumes to find mates. (And there was a similar study done recently here.)
"Instead of running a traditional laboratory wind-tunnel experiment, we used a complementary 'in-silico' approach using artificial neural networks," Singh explained. "This helped us develop an integrative understanding of plume tracking across multiple levels, including emergent behavior, neural representation and neural dynamics."To train their plume-tracking agents using DRL, the researchers first simulated an odor emanating from a source located within a windy arena with a total area of approximately 120 m2. When their agents identified where the source of the odor was located, they received a reward. In contrast, if they lost track of the odor plume and left the arena, they were "punished.""The behavior that emerges in our trained artificial agents bears a striking resemblance to the behavior modules biologists have previously observed in flying insects performing plume tracking," Singh said.
via University of Washington and University of Nevada: Satpreet H. Singh et al, Emergent behaviour and neural dynamics in artificial agents tracking odour plumes, Nature Machine Intelligence (2023). DOI: 10.1038/s42256-022-00599-w
Image credit: AI Art - Total Hallucination - 2023
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