K10-Unit_7-Introduction_to_Multi_Agents_and_AI_vs_AI-A0-Introduction

中英文对照学习，效果更佳！
原课程链接：https://huggingface.co/deep-rl-course/unitbonus1/introduction?fw=pt

Introduction

引言

Since the beginning of this course, we learned to train agents in a single-agent system where our agent was alone in its environment: it was not cooperating or collaborating with other agents.

从本课程开始，我们学习了在单代理系统中培训代理，在这种系统中，我们的代理在其环境中是单独的：它不与其他代理合作或协作。

This worked great, and the single-agent system is useful for many applications.

这很有效，单代理系统对许多应用程序都很有用。

A patchwork of all the environments you’ve trained your agents on since the beginning of the course

拼凑自本课程开始以来您培训代理的所有环境拼凑而成

But, as humans, we live in a multi-agent world. Our intelligence comes from interaction with other agents. And so, our goal is to create agents that can interact with other humans and other agents.

但是，作为人类，我们生活在一个多主体的世界里。我们的情报来自与其他特工的互动。因此，我们的目标是创建能够与其他人类和其他代理交互的代理。

Consequently, we must study how to train deep reinforcement learning agents in a multi-agents system to build robust agents that can adapt, collaborate, or compete.

因此，我们必须研究如何在多智能体系统中训练深度强化学习智能体，以构建具有自适应、协作和竞争能力的健壮智能体。

So today, we’re going to learn the basics of this fascinating topic of multi-agents reinforcement learning (MARL).

因此，今天，我们将学习多智能体强化学习(MAIL)这个有趣话题的基础知识。

And the most exciting part is that during this unit, you’re going to train your first agents in a multi-agents system: a 2vs2 soccer team that needs to beat the opponent team.

最令人兴奋的是，在这个单元中，你将在一个多代理系统中训练你的第一个代理：一支需要击败对手的2vs2足球队。

And you’re going to participate in AI vs. AI challenge where your trained agent will compete against other classmates’ agents every day and be ranked on a new leaderboard.

你将参加AI VS AI挑战，在那里你训练有素的代理将每天与其他同学的代理竞争，并在新的排行榜上排名。

This environment was made by the Unity MLAgents Team
So let’s get started!

SoccerTwos这个环境是由Unity MLAgents团队创建的，所以让我们开始吧！