{"id":12477,"date":"2024-11-09T10:18:53","date_gmt":"2024-11-09T10:18:53","guid":{"rendered":"https:\/\/bvcoend.ac.in\/?page_id=12477"},"modified":"2024-11-09T10:18:53","modified_gmt":"2024-11-09T10:18:53","slug":"rl-lab","status":"publish","type":"page","link":"https:\/\/bvcoend.ac.in\/index.php\/rl-lab\/","title":{"rendered":"RL Lab"},"content":{"rendered":"<h2><span style=\"color: #000000;\">Reinforcement Learning Lab<\/span><\/h2>\n<p>&nbsp;<\/p>\n<p><span style=\"color: #000000;\"><strong>Subject Code-ML 409P <\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>Introduction<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">A Reinforcement Learning (RL) Lab provides a hands-on environment for students, researchers, and practitioners to explore and experiment with reinforcement learning algorithms. The lab allows individuals to better understand the theoretical concepts of RL and gain practical experience by implementing and testing different RL techniques in a controlled, interactive setting.The goal of an RL lab is to bridge the gap between theory and practice, providing tools, environments, and problems that illustrate the core principles of reinforcement learning, such as decision-making, reward maximization, policy optimization, and agent-environment interaction.<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>Objective of the Laboratory<\/strong><\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">To introduce the foundation of Reinforcement learning foundation and Q Network algorithm) To understand with AI demonstration that intelligence requires ability to find reason.<\/span><\/li>\n<li><span style=\"color: #000000;\">To understand policy optimization ,recent advanced techniques and applications of Reinforcement learning.<\/span><\/li>\n<li><span style=\"color: #000000;\">To introduce the concept of deep learning and neural network.<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\"><strong>Facilities<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Software:ANACONDA<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 People<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Faculty Coordinator: Ms. Nupur<\/span><\/p>\n<p><span style=\"color: #000000;\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Lab Technician: Mrs. Yashoda rani<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Reinforcement Learning Lab &nbsp; Subject Code-ML 409P Introduction A Reinforcement Learning (RL) Lab provides a hands-on environment for students, researchers, and practitioners to explore and experiment with reinforcement learning algorithms. The lab allows individuals to better understand the theoretical concepts of RL and gain practical experience by implementing and testing different RL techniques in a&hellip;<\/p>\n","protected":false},"author":11,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/bvcoend.ac.in\/index.php\/wp-json\/wp\/v2\/pages\/12477"}],"collection":[{"href":"https:\/\/bvcoend.ac.in\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/bvcoend.ac.in\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/bvcoend.ac.in\/index.php\/wp-json\/wp\/v2\/users\/11"}],"replies":[{"embeddable":true,"href":"https:\/\/bvcoend.ac.in\/index.php\/wp-json\/wp\/v2\/comments?post=12477"}],"version-history":[{"count":1,"href":"https:\/\/bvcoend.ac.in\/index.php\/wp-json\/wp\/v2\/pages\/12477\/revisions"}],"predecessor-version":[{"id":12478,"href":"https:\/\/bvcoend.ac.in\/index.php\/wp-json\/wp\/v2\/pages\/12477\/revisions\/12478"}],"wp:attachment":[{"href":"https:\/\/bvcoend.ac.in\/index.php\/wp-json\/wp\/v2\/media?parent=12477"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}