• Corpus ID: 247763011

Unentangled quantum reinforcement learning agents in the OpenAI Gym

@inproceedings{Hsiao2022UnentangledQR,
  title={Unentangled quantum reinforcement learning agents in the OpenAI Gym},
  author={Jen-Yueh Hsiao and Yuxuan Du and Wei-Yin Chiang and Min-Hsiu Hsieh and Hsi-Sheng Goan},
  year={2022}
}
Classical reinforcement learning (RL) has generated excellent results in different regions ; however, its sample inefficiency remains a critical issue. In this paper, we provide concrete numerical evidence that the sample efficiency (the speed of convergence) of quantum RL could be better than that of classical RL, and for achieving comparable learning performance, quantum RL could use much (at least one order of magnitude) fewer trainable parameters than classical RL. Specifically, we employ the… 

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