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Multi-robot based gas source localization (GSL) in turbulence dominated airflow environments is addressed. A multi-agent reinforcement learning (RL) algorithm is proposed for training multiple robots to finish the GSL task. To improve searching efficiency, the strategy-sharing based RL algorithm is implemented for the GSL task in three different large-scale advection-diffusion simulated plume environments...
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