From Multi-agent to Multi-robot: A Scalable Training and Evaluation Platform for Multi-robot Reinforcement Learning

@article{Liang2022FromMT,
  title={From Multi-agent to Multi-robot: A Scalable Training and Evaluation Platform for Multi-robot Reinforcement Learning},
  author={Zhiuxan Liang and Jiannong Cao and Shan Jiang and Divya Saxena and Jinlin Chen and Huafeng Xu},
  journal={ArXiv},
  year={2022},
  volume={abs/2206.09590}
}
—Multi-agent reinforcement learning (MARL) has been gaining extensive attention from academia and industries in the past few decades. One of the fundamental problems in MARL is how to evaluate different approaches comprehensively. Most existing MARL methods are evaluated in either video games or simplistic simulated scenarios. It remains unknown how these methods perform in real-world scenarios, especially multi-robot systems. This paper introduces a scalable emulation platform for multi-robot… 

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