This is about multiplayer reinforcement learning, if you will.

这是一项多人强化学习任务。

This algorithm was based on a combination of a neural network and reinforcement learning.

该算法基于神经网络和强化学习的结合。

The goal was to learn to perform a backflip through reinforcement learning.

目标是通过强化学习来学习表演后空翻。

The DeepMind researchers worked out an ingenious way to plug this preference for novelty into reinforcement learning.

DeepMind 研究人员找到巧妙的方法将这种对新奇事物的偏好插入到强化学习中。

Researchers used a technique called reinforcement learning where they gave robots cooperative tasks instead of competitive ones.

研究人员使用了一种叫做强化学习的技术，他们给机器人合作任务，而不是竞争任务。

That software was a piece of artificial intelligence called a deep evolutionary reinforcement learning algorithm, or derl.

该软件是一款人工智能软件，叫做深度进化强化学习算法，简称derl。

We don't know how the RLHF reinforcement learning works, we don't know what other gadgets are in there.

我们不知道 RLHF 强化学习是如何工作的，我们不知道里面还有什么其他的小工具。

By applying the evolved neural circuits, the researchers construct spiking neural networks for image classification and reinforcement learning tasks.

通过应用进化的神经环路，研究人员构建了用于图像分类和强化学习任务的脉冲神经网络。

It's an example that doesn't work two weeks later because they're constantly changing things with reinforcement learning and so forth.

这个例子两周后就不成立了，因为他们通过强化学习等不断进行改变。

Reinforcement learning is great for that but it isn't perfect in every situation.

强化学习对此非常有用，但并非在所有情况下都是完美的。

Everything is learned from scratch with a few small modifications to the reinforcement learning algorithm.

所有结果都是通过对于增强学习算法的一个小调整从无到有学出来的。

The neural network was used to understand the video feed, and reinforcement learning is there to come up with the appropriate actions.

神经网络用于理解视频画面的输入，强化学习则会提出合适的对策行为。

A really cool piece of work that can potentially open up new ways of thinking about reinforcement learning.

这真的是一篇很棒的文章，它可能会开启一种新的思考强化学习的方式。

Combined with on-policy and off-policy deep reinforcement learning algorithms, NeuEvo achieves comparable performance with artificial neural networks, as shown in the study.

结合政策内外深度强化学习算法，NeuEvo 实现了与人工神经网络相当的性能，如研究所示。

This is where deep reinforcement learning comes in.

这就是深度强化学习的用武之地。

This work is a collaboration between OpenAI and DeepMind's security team and is about introducing more human control in reinforcement learning problems.

这篇论文由 OpenAI 和 DeepMind 的安全小组合作完成，目标是在强化学习问题中引入更多人为控制。

The key factors to make this happen is to apply two modifications to the original reinforcement learning algorithm.

关键点就是在原始增强学习算法上增加两项调整。

In a reinforcement learning problem, he is our agent, and he's trying to learn a policy - that is, how to interact with his environment.

在强化学习问题中，他是我们的代理，他正在尝试学习策略 - 即如何与他的环境交互。

The Meta team's crucial contribution was therefore to augment reinforcement learning with natural-language processing.

因此，该团队做出的关键贡献是利用自然语言处理来增强强化学习。

We will not be able to use reinforcement learning with human feedback to hardwire its values into it.

我们将无法使用带有人类反馈的强化学习来将其价值观硬连接到其中。