深度强化学习 - 翻译成英语

deep reinforcement learning
deep RL

在 中文 中使用 深度强化学习 的示例及其翻译为 英语

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报道称,Facebook的AI团队通过将搜索技术与深度强化学习结合起来实现了这一壮举。
Facebook's AI team achieved the feat by applying search techniques in conjunction with deep reinforcement learning.
这家总部位于加州伯克利的初创公司正在构建一个通用的、深度强化学习平台,供企业使用机器人和引擎等工业控制系统。
The Berkeley, California-based startup is building a general-purpose, deep reinforcement learning platform for enterprises to use with industrial control systems such as robotics and engines.
深度强化学习.
Deep reinforcement learning.
长颈鹿:使用深度强化学习下棋.
Giraffe: Using deep reinforcement learning to play chess.
深度强化学习也是AlphaGo的核心。
Deep reinforcement learning is the core of AlphaGo.
近年最酷成果都来自深度强化学习.
The coolest results in recent years have come from deep reinforcement learning.
深度强化学习的范围是巨大的。
The scope of deep learning is immense.
从人类偏好中学习的深度强化学习》.
Deep Reinforcement Learning from Human Preferences.
深度强化学习是人工智能研究的前沿。
Deep reinforcement learning is at the forefront of AI research.
这也是我对深度强化学习的大致感受。
That's roughly how I feel about deep reinforcement learning.
深度强化学习确实做了许多很酷的事情。
Deep reinforcement learning has certainly done some very cool things.
强化学习跟深度学习结合,就叫深度强化学习
Using deep learning with reinforcement learning is called deep reinforcement learning.
目前深度强化学习研究领域仍然存在着挑战。
There are many challenges in current reinforcement learning research.
深度强化学习确实做了一些非常酷的事情。
Deep reinforcement learning has certainly done some very cool things.
深度强化学习是强化学习(RL)和深度学习的组合。
Deep reinforcement learning is the combination of reinforcement learning(RL) and deep learning..
Apple、Facebook和Google都在投资研发深度强化学习
Apple, Facebook, and Google are investing in deep reinforcement learning.
深度强化学习的最终目标是从像素中学会控制策略;.
The end-goal of deep reinforcement learning is to learn the control policy directly from pixels;
什么是深度强化学习:人工智能和深度学习的下一.
What is deep reinforcement learning: The next step in AI and deep learning..
目前深度强化学习技术主要应用在一些游戏、比赛中。
At present, deep reinforcement learning technology is mainly used in some games and competitions.".
基于模型的深度强化学习(涉及到无监管预测型学习)。
Deep model-based reinforcement learning(which involved unsupervised predictive learning).
结果: 168, 时间: 0.0171

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