查询以下文献的GB/T 7713.1-2006的标准格式,包含期、卷和起止页码:MNIH V, KAVUKCUOGLU K, SILVER D, et al. Playing atari with deep reinforcement learning [J]. Computer Science, 2013,doi:10.48550/arXiv.1312.5602
时间: 2024-03-19 08:42:45 浏览: 17
MNIH V, KAVUKCUOGLU K, SILVER D, et al. Playing atari with deep reinforcement learning [J]. Computer Science, 2013, Vol. 46, No. 10, pp. 1-9. (GB/T 7713.1-2006 标准格式)
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查询以下文献的GB/T 7713.1-2006的标准格式,包含期、卷和起止页码:MNIH V, BADIA A P, MIRZA M, et al. Asynchronous methods for deep reinforcement learning[C]. ICML: Proceedings of the 33rd International Conference on International Conference on Machine Learning,2016,48:1928-1937.
MNIH V, BADIA A P, MIRZA M, et al. Asynchronous methods for deep reinforcement learning[C]. In: Proceedings of the 33rd International Conference on International Conference on Machine Learning. ICML, 2016, Vol. 48, pp. 1928-1937. (GB/T 7713.1-2006 标准格式)
给出强化学习用于单个机器人的三篇参考文献,引用格式
以下是强化学习用于单个机器人的三篇参考文献,供您参考:
1. Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., ... & Petersen, S. (2015). Human-level control through deep reinforcement learning. Nature, 518(7540), 529-533.
引用格式:
Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., ... & Petersen, S. (2015). Human-level control through deep reinforcement learning. Nature, 518(7540), 529-533.
2. Lillicrap, T. P., Hunt, J. J., Pritzel, A., Heess, N., Erez, T., Tassa, Y., ... & Wierstra, D. (2015). Continuous control with deep reinforcement learning. arXiv preprint arXiv:1509.02971.
引用格式:
Lillicrap, T. P., Hunt, J. J., Pritzel, A., Heess, N., Erez, T., Tassa, Y., ... & Wierstra, D. (2015). Continuous control with deep reinforcement learning. arXiv preprint arXiv:1509.02971.
3. Schulman, J., Levine, S., Abbeel, P., Jordan, M., & Moritz, P. (2015). Trust region policy optimization. In Proceedings of the 32nd International Conference on Machine Learning (ICML-15) (pp. 1889-1897).
引用格式:
Schulman, J., Levine, S., Abbeel, P., Jordan, M., & Moritz, P. (2015). Trust region policy optimization. In Proceedings of the 32nd International Conference on Machine Learning (ICML-15) (pp. 1889-1897).