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- W4382318788 abstract "Multi-agent pathfinding (MAPF) is essential to large-scale robotic coordination tasks. Planning-based algorithms show their advantages in collision avoidance while avoiding exponential growth in the number of agents. Reinforcement-learning (RL)-based algorithms can be deployed efficiently but cannot prevent collisions entirely due to the lack of hard constraints. This paper combines the merits of planning-based and RL-based MAPF methods to propose a deployment-efficient and collision-free MAPF algorithm. The experiments show the effectiveness of our approach." @default.
- W4382318788 created "2023-06-28" @default.
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- W4382318788 date "2023-06-26" @default.
- W4382318788 modified "2023-09-23" @default.
- W4382318788 title "Towards Deployment-Efficient and Collision-Free Multi-Agent Path Finding (Student Abstract)" @default.
- W4382318788 doi "https://doi.org/10.1609/aaai.v37i13.26951" @default.
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