  Navigation of male moths toward females during the mating search offers a
unique perspective on the exploration-exploitation (EE) model in
decision-making. This study uses the EE model to explain male moth
pheromone-driven flight paths. We leverage wind tunnel measurements and 3D
tracking using infrared cameras to gain insights into male moth behavior.
During the experiments in the wind tunnel, we add disturbance to the airflow
and analyze the effect of increased fluctuations on moth flights in the context
of the proposed EE model. We separate the exploration and exploitation phases
by applying a genetic algorithm to the dataset of moth 3D trajectories. First,
we demonstrate that the exploration-to-exploitation rate (EER) increases with
distance from the source of the female pheromone, which can be explained in the
context of the EE model. Furthermore, our findings reveal a compelling
relationship between EER and increased flow fluctuations near the pheromone
source. Using the open-source pheromone plume simulation and our moth-inspired
navigation model, we explain why male moths exhibit an enhanced EER as
turbulence levels increase, emphasizing the agent's adaptation to dynamically
changing environments. This research extends our understanding of optimal
navigation strategies based on general biological EE models and supports the
development of advanced, theoretically supported bio-inspired navigation
algorithms. We provide important insights into the potential of bio-inspired
navigation models for addressing complex decision-making challenges.
