{"version":"1.0","provider_name":"Glosarix","provider_url":"https:\/\/glosarix.com\/en\/","author_name":"Team Glosarix","author_url":"https:\/\/glosarix.com\/en\/author\/adm_glosarix\/","title":"Max-Q - Glosarix","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"CL8LwxV20n\"><a href=\"https:\/\/glosarix.com\/en\/glossary\/max-q-en\/\">Max-Q<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/glosarix.com\/en\/glossary\/max-q-en\/embed\/#?secret=CL8LwxV20n\" width=\"600\" height=\"338\" title=\"&#8220;Max-Q&#8221; &#8212; Glosarix\" data-secret=\"CL8LwxV20n\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/glosarix.com\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","description":"Description: Max-Q is a hierarchical reinforcement learning algorithm that focuses on breaking down the value function into smaller, manageable components. This approach allows reinforcement learning agents to tackle complex problems by dividing them into simpler subproblems, thereby facilitating decision-making in environments with multiple levels of abstraction. The central idea behind Max-Q is that by decomposing [&hellip;]"}