deep-rl-course/pr_617/en/unit7/introduction.html

<meta charset="utf-8" /><meta name="hf:doc:metadata" content="{&quot;title&quot;:&quot;Introduction&quot;,&quot;local&quot;:&quot;introduction&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Course Maintenance Notice 🚧&quot;,&quot;local&quot;:&quot;course-maintenance-notice-&quot;,&quot;sections&quot;:[],&quot;depth&quot;:2}],&quot;depth&quot;:1}">
		<link href="/docs/deep-rl-course/pr_617/en/_app/immutable/assets/0.e3b0c442.css" rel="modulepreload">
		<link rel="modulepreload" href="/docs/deep-rl-course/pr_617/en/_app/immutable/entry/start.9ed444ad.js">
		<link rel="modulepreload" href="/docs/deep-rl-course/pr_617/en/_app/immutable/chunks/scheduler.37c15a92.js">
		<link rel="modulepreload" href="/docs/deep-rl-course/pr_617/en/_app/immutable/chunks/singletons.a441b123.js">
		<link rel="modulepreload" href="/docs/deep-rl-course/pr_617/en/_app/immutable/chunks/index.18351ede.js">
		<link rel="modulepreload" href="/docs/deep-rl-course/pr_617/en/_app/immutable/chunks/paths.04916d33.js">
		<link rel="modulepreload" href="/docs/deep-rl-course/pr_617/en/_app/immutable/entry/app.adbc0488.js">
		<link rel="modulepreload" href="/docs/deep-rl-course/pr_617/en/_app/immutable/chunks/index.7cb9c9b8.js">
		<link rel="modulepreload" href="/docs/deep-rl-course/pr_617/en/_app/immutable/nodes/0.b869a19a.js">
		<link rel="modulepreload" href="/docs/deep-rl-course/pr_617/en/_app/immutable/chunks/each.e59479a4.js">
		<link rel="modulepreload" href="/docs/deep-rl-course/pr_617/en/_app/immutable/nodes/74.ad77ae2d.js">
		<link rel="modulepreload" href="/docs/deep-rl-course/pr_617/en/_app/immutable/chunks/index.e79b7fff.js"><!-- HEAD_svelte-u9bgzb_START --><meta name="hf:doc:metadata" content="{&quot;title&quot;:&quot;Introduction&quot;,&quot;local&quot;:&quot;introduction&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Course Maintenance Notice 🚧&quot;,&quot;local&quot;:&quot;course-maintenance-notice-&quot;,&quot;sections&quot;:[],&quot;depth&quot;:2}],&quot;depth&quot;:1}"><!-- HEAD_svelte-u9bgzb_END -->      <p></p>  <h1 class="relative group"><a id="introduction" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#introduction"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Introduction</span></h1> <img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit0/thumbnail.png" alt="Thumbnail"> <p data-svelte-h="svelte-smsux1">Since the beginning of this course, we learned to train agents in a <em>single-agent system</em>  where our agent was alone in its environment: it was <strong>not cooperating or collaborating with other agents</strong>.</p> <p data-svelte-h="svelte-e9caw3">This worked great, and the single-agent system is useful for many applications.</p> <figure data-svelte-h="svelte-so1y2c"><img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit10/patchwork.jpg" alt="Patchwork"> <figcaption>A patchwork of all the environments you’ve trained your agents on since the beginning of the course</figcaption></figure> <p data-svelte-h="svelte-nf786x">But, as humans, <strong>we live in a multi-agent world</strong>. Our intelligence comes from interaction with other agents. And so, our <strong>goal is to create agents that can interact with other humans and other agents</strong>.</p> <p data-svelte-h="svelte-5dt70f">Consequently, we must study how to train deep reinforcement learning agents in a <em>multi-agents system</em> to build robust agents that can adapt, collaborate, or compete.</p> <p data-svelte-h="svelte-19g4sgk">So today we’re going to <strong>learn the basics of the fascinating topic of multi-agents reinforcement learning (MARL)</strong>.</p> <p data-svelte-h="svelte-ywv0q0">And the most exciting part is that, during this unit, you’re going to train your first agents in a multi-agents system: <strong>a 2vs2 soccer team that needs to beat the opponent team</strong>.</p>  <h2 class="relative group"><a id="course-maintenance-notice-" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#course-maintenance-notice-"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Course Maintenance Notice 🚧</span></h2> <p data-svelte-h="svelte-4ejbxo">Please note that this <strong>Deep Reinforcement Learning course is now in a low-maintenance state</strong>. However, it <strong>remains an excellent resource to learn both the theory and practical aspects of Deep Reinforcement Learning</strong>.</p> <p data-svelte-h="svelte-6itumt">Keep in mind the following points:</p> <ul data-svelte-h="svelte-58atrv"><li><em>Unit 7 (AI vs AI)</em> : This feature is currently non-functional. However, you can still train your agent to play soccer and observe its performance. But the leaderboard for AI vs AI soccer was shut down.</li></ul> <figure data-svelte-h="svelte-100gprn"><img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit10/soccertwos.gif" alt="SoccerTwos"> <figcaption>This environment was made by the <a href="https://github.com/Unity-Technologies/ml-agents">Unity MLAgents Team</a></figcaption></figure> <p data-svelte-h="svelte-2tvssp">So let’s get started!</p> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/deep-rl-class/blob/main/units/en/unit7/introduction.mdx" target="_blank"><span data-svelte-h="svelte-1kd6by1">&lt;</span> <span data-svelte-h="svelte-x0xyl0">&gt;</span> <span data-svelte-h="svelte-1dajgef"><span class="underline ml-1.5">Update</span> on GitHub</span></a>  <p></p> 
			
			<script>
				{
					__sveltekit_403nbm = {
						assets: "/docs/deep-rl-course/pr_617/en",
						base: "/docs/deep-rl-course/pr_617/en",
						env: {}
					};

					const element = document.currentScript.parentElement;

					const data = [null,null];

					Promise.all([
						import("/docs/deep-rl-course/pr_617/en/_app/immutable/entry/start.9ed444ad.js"),
						import("/docs/deep-rl-course/pr_617/en/_app/immutable/entry/app.adbc0488.js")
					]).then(([kit, app]) => {
						kit.start(app, element, {
							node_ids: [0, 74],
							data,
							form: null,
							error: null
						});
					});
				}
			</script>