Cooperatively pursuing a target unmanned aerial vehicle by multiple unmanned aerial vehicles based on multiagent reinforcement learning
This article considers a pursuit‐evasion problem, in which multiple unmanned aerial vehicles (multi‐UAVs) are required to cooperatively pursue a moving target UAV. The dynamics of the three‐dimensional partially unknown environment makes it hard to deal with this problem. A multiagent reinforcement learning approach is proposed. This algorithm is extended from cooperative double Q‐learning by taking into account of the characteristics of the studied pursuit problem. To study the performance, a simulator is developed, which concerns the dynamic nature of the environment and flight constraints of UAV. Compared with several state‐of‐the‐art reinforcement learning algorithms, the proposed algorithm provides better policy such that the pursuing multi‐UAVs can effectively chase the moving target UAV.
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Cooperatively pursuing a target unmanned aerial vehicle by multiple unmanned aerial vehicles based on multiagent reinforcement learning
Semantic Scholar · Engineering · 2020
Abstract
This article considers a pursuit‐evasion problem, in which multiple unmanned aerial vehicles (multi‐UAVs) are required to cooperatively pursue a moving target UAV. The dynamics of the three‐dimensional partially unknown environment makes it hard to deal with this problem. A multiagent reinforcement learning approach is proposed. This algorithm is extended from cooperative double Q‐learning by taking into account of the characteristics of the studied pursuit problem. To study the performance, a simulator is developed, which concerns the dynamic nature of the environment and flight constraints of UAV. Compared with several state‐of‐the‐art reinforcement learning algorithms, the proposed algorithm provides better policy such that the pursuing multi‐UAVs can effectively chase the moving target UAV.