An Introduction to Quantum Reinforcement Learning (QRL)
<|reference_start|>An Introduction to Quantum Reinforcement Learning (QRL): Recent advancements in quantum computing (QC) and machine learning (ML) have sparked considerable interest in the integration of these two cutting-edge fields. Among the various ML techniques, reinforcement learning (RL) stands out for its ability to address complex sequential decision-making problems. RL has already demonstrated substantial success in the classical ML community. Now, the emerging field of Quantum Reinforcement Learning (QRL) seeks to enhance RL algorithms by incorporating principles from quantum computing. This paper offers an introduction to this exciting area for the broader AI and ML community.<|reference_end|>
@article{chen2024an,
    title={An Introduction to Quantum Reinforcement Learning (QRL)},
    author={Samuel Yen-Chi Chen},
    journal={arXiv preprint arXiv:2409.05846},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.05846},
    primaryClass={quant-ph cs.AI cs.ET cs.LG cs.NE}
}