{"id":4,"date":"2008-07-15T00:10:17","date_gmt":"2008-07-14T22:10:17","guid":{"rendered":"http:\/\/blog.teleranek.org\/?p=4"},"modified":"2025-06-29T12:29:30","modified_gmt":"2025-06-29T10:29:30","slug":"bayesian-net-artificial-intelligence-sim","status":"publish","type":"post","link":"https:\/\/blog.teleranek.org\/?p=4","title":{"rendered":"Bayesian net Artificial Intelligence sim"},"content":{"rendered":"<p>I&#8217;ve decided not to add this project to my portfolio, because it&#8217;s more complex and needs some words of explanation on this blog. It&#8217;s main purpose is to simulate different algorithms used in AI programming. It does so, by applying bayesian nets to agents ( cube-like robots ). Each agent as it is seen on simulation, eats little blue cubes. They have 3 states of hunger &#8211; 3 = not hungry, 2 = hungry, 1 = v.hungry. Each robot can shoot, but shooting makes them more hungry. Robot shoots towards his oponent only if the oponent is in robot&#8217;s range of sight, and if the robot isn&#8217;t very hungry.<\/p>\n<p>When food and enemy isn&#8217;t visible to the robot, robot simply walks around doing nothing. Each robot has its bayesian net which decides what to do &#8211; shoot enemy, eat , run from enemy and shoot, and so on. You can tech your own robot, by clicking &#8220;add human&#8221; and eating or shooting by yourself. Then, when you click &#8220;learn&#8221;, AI takes control of your robot and tries to imitate your moves.<\/p>\n<p>Button called &#8220;decrobo&#8221; places new robot driven by decision network. It takes time to learn for the first time.<\/p>\n<p><a href=\"http:\/\/exp.teleranek.org\/bayes\/index.html\" target=\"_blank\" rel=\"noopener noreferrer\"><img decoding=\"async\" class=\"alignnone\" src=\"http:\/\/exp.teleranek.org\/bayes\/bayes.jpg\" alt=\"\" \/><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>I&#8217;ve decided not to add this project to my portfolio, because it&#8217;s more complex and needs some words of explanation on this blog. It&#8217;s main purpose is to simulate different algorithms used in AI programming. It does so, by applying bayesian nets to agents ( cube-like robots ). Each agent as it is seen on [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[26,25,18,27,11],"class_list":["post-4","post","type-post","status-publish","format-standard","hentry","category-flash-experiments","tag-ai","tag-artificial-intelligence","tag-as3","tag-bayesian-network","tag-pv3d"],"_links":{"self":[{"href":"https:\/\/blog.teleranek.org\/index.php?rest_route=\/wp\/v2\/posts\/4","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.teleranek.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.teleranek.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.teleranek.org\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.teleranek.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=4"}],"version-history":[{"count":1,"href":"https:\/\/blog.teleranek.org\/index.php?rest_route=\/wp\/v2\/posts\/4\/revisions"}],"predecessor-version":[{"id":369,"href":"https:\/\/blog.teleranek.org\/index.php?rest_route=\/wp\/v2\/posts\/4\/revisions\/369"}],"wp:attachment":[{"href":"https:\/\/blog.teleranek.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.teleranek.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.teleranek.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}