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The Multi-Agent Pickup and Delivery Problem: MAPF, MARL and Its Warehouse Applications

2022-03-14 · Tim Tsz-Kit Lau, Biswa Sengupta

We study two state-of-the-art solutions to the multi-agent pickup and delivery (MAPD) problem based on different principles -- multi-agent path-finding (MAPF) and multi-agent reinforcement learning (MARL). Specifically, a recent MAPF algorithm called conflict-based search (CBS) and a current MARL algorithm called shared experience actor-critic (SEAC) are studied. While the performance of these algorithms is measured using quite different metrics in their separate lines of work, we aim to benchmark these two methods comprehensively in a simulated warehouse automation environment.

📄 PDF Abstract BibTeX arXiv:2203.07092

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Tasks

Multi-Agent Path FindingMulti-agent Reinforcement Learningreinforcement-learningReinforcement Learning (RL)

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