{"version":"1.0","provider_name":"Artemis","provider_url":"https:\/\/modelos.aipublica.com.br\/artemis2","author_name":"Ney Barbosa","author_url":"https:\/\/modelos.aipublica.com.br\/artemis2\/author\/ney\/","title":"Markov Chains: Memoryless Paths in Random Movement - Artemis","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"EXtTNALGWH\"><a href=\"https:\/\/modelos.aipublica.com.br\/artemis2\/markov-chains-memoryless-paths-in-random-movement\/\">Markov Chains: Memoryless Paths in Random Movement<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/modelos.aipublica.com.br\/artemis2\/markov-chains-memoryless-paths-in-random-movement\/embed\/#?secret=EXtTNALGWH\" width=\"600\" height=\"338\" title=\"&#8220;Markov Chains: Memoryless Paths in Random Movement&#8221; &#8212; Artemis\" data-secret=\"EXtTNALGWH\" 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:\/\/modelos.aipublica.com.br\/artemis2\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","description":"Markov chains are foundational models in probability theory, describing systems that evolve through discrete states where the next state depends solely on the current state\u2014not on the sequence of prior steps. This memoryless property enables elegant, efficient modeling of random processes, especially in dynamic movement such as the immersive game Crazy Time. At its core, [&hellip;]"}