Buckets:

hf-doc-build
/

doc-dev

Files

xet

hf-doc-build/doc-dev / deep-rl-course /pr_592 /en /unit2 /additional-readings.html

rtrm

about 2 months ago

download

raw

7.49 kB

	<meta charset="utf-8" /><meta name="hf:doc:metadata" content="{"title":"Additional Readings","local":"additional-readings","sections":[{"title":"Monte Carlo and TD Learning","local":"mc-td","sections":[],"depth":2},{"title":"Q-Learning","local":"q-learning","sections":[],"depth":2}],"depth":1}">
	<link href="/docs/deep-rl-course/pr_592/en/_app/immutable/assets/0.e3b0c442.css" rel="modulepreload">
	<link rel="modulepreload" href="/docs/deep-rl-course/pr_592/en/_app/immutable/entry/start.f0057f74.js">
	<link rel="modulepreload" href="/docs/deep-rl-course/pr_592/en/_app/immutable/chunks/scheduler.37c15a92.js">
	<link rel="modulepreload" href="/docs/deep-rl-course/pr_592/en/_app/immutable/chunks/singletons.8a49a196.js">
	<link rel="modulepreload" href="/docs/deep-rl-course/pr_592/en/_app/immutable/chunks/index.18351ede.js">
	<link rel="modulepreload" href="/docs/deep-rl-course/pr_592/en/_app/immutable/chunks/paths.7343a278.js">
	<link rel="modulepreload" href="/docs/deep-rl-course/pr_592/en/_app/immutable/entry/app.596d7feb.js">
	<link rel="modulepreload" href="/docs/deep-rl-course/pr_592/en/_app/immutable/chunks/index.7cb9c9b8.js">
	<link rel="modulepreload" href="/docs/deep-rl-course/pr_592/en/_app/immutable/nodes/0.ce5f0bd8.js">
	<link rel="modulepreload" href="/docs/deep-rl-course/pr_592/en/_app/immutable/chunks/each.e59479a4.js">
	<link rel="modulepreload" href="/docs/deep-rl-course/pr_592/en/_app/immutable/nodes/21.2d035e78.js">
	<link rel="modulepreload" href="/docs/deep-rl-course/pr_592/en/_app/immutable/chunks/EditOnGithub.858acfec.js"><!-- HEAD_svelte-u9bgzb_START --><meta name="hf:doc:metadata" content="{"title":"Additional Readings","local":"additional-readings","sections":[{"title":"Monte Carlo and TD Learning","local":"mc-td","sections":[],"depth":2},{"title":"Q-Learning","local":"q-learning","sections":[],"depth":2}],"depth":1}"><!-- HEAD_svelte-u9bgzb_END --> <p></p> <h1 class="relative group"><a id="additional-readings" 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="#additional-readings"><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>Additional Readings</span></h1> <p data-svelte-h="svelte-19yxmer">These are <strong>optional readings</strong> if you want to go deeper.</p> <h2 class="relative group"><a id="mc-td" 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="#mc-td"><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>Monte Carlo and TD Learning</span></h2> <p data-svelte-h="svelte-9xq7la">To dive deeper into Monte Carlo and Temporal Difference Learning:</p> <ul data-svelte-h="svelte-c10bab"><li><a href="https://stats.stackexchange.com/questions/355820/why-do-temporal-difference-td-methods-have-lower-variance-than-monte-carlo-met">Why do temporal difference (TD) methods have lower variance than Monte Carlo methods?</a></li> <li><a href="https://stats.stackexchange.com/questions/336974/when-are-monte-carlo-methods-preferred-over-temporal-difference-ones">When are Monte Carlo methods preferred over temporal difference ones?</a></li></ul> <h2 class="relative group"><a id="q-learning" 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="#q-learning"><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>Q-Learning</span></h2> <ul data-svelte-h="svelte-i2a184"><li><a href="http://incompleteideas.net/book/RLbook2020.pdf">Reinforcement Learning: An Introduction, Richard Sutton and Andrew G. Barto Chapter 5, 6 and 7</a></li> <li><a href="https://youtu.be/Psrhxy88zww">Foundations of Deep RL Series, L2 Deep Q-Learning by Pieter Abbeel</a></li></ul> <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/unit2/additional-readings.mdx" target="_blank"><span data-svelte-h="svelte-1kd6by1"><</span> <span data-svelte-h="svelte-x0xyl0">></span> <span data-svelte-h="svelte-1dajgef"><span class="underline ml-1.5">Update</span> on GitHub</span></a> <p></p>

	<script>
	{
	__sveltekit_mhj5y4 = {
	assets: "/docs/deep-rl-course/pr_592/en",
	base: "/docs/deep-rl-course/pr_592/en",
	env: {}
	};

	const element = document.currentScript.parentElement;

	const data = [null,null];

	Promise.all([
	import("/docs/deep-rl-course/pr_592/en/_app/immutable/entry/start.f0057f74.js"),
	import("/docs/deep-rl-course/pr_592/en/_app/immutable/entry/app.596d7feb.js")
	]).then(([kit, app]) => {
	kit.start(app, element, {
	node_ids: [0, 21],
	data,
	form: null,
	error: null
	});
	});
	}
	</script>

Xet Storage Details

Size:: 7.49 kB
Xet hash:: c7a7b5fe0183845e53042f0f53b4d6af9f5465f66383e1ad3a48c2b479c3a5ae

Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.