{"id":14752,"date":"2019-05-03T12:42:14","date_gmt":"2019-05-03T16:42:14","guid":{"rendered":"http:\/\/bangla.salearningschool.com\/recent-posts\/ai-implementation-platforms-reinforcement-learning-platforms-and-applications\/"},"modified":"2019-05-03T12:42:14","modified_gmt":"2019-05-03T16:42:14","slug":"ai-implementation-platforms-reinforcement-learning-platforms-and-applications","status":"publish","type":"post","link":"http:\/\/bangla.sitestree.com\/?p=14752","title":{"rendered":"AI Implementation Platforms: Reinforcement Learning Platforms and Applications:"},"content":{"rendered":"<p>&quot;<\/p>\n<h1>Gym:<br \/>\n<a href=\"https:\/\/gym.openai.com\/\">https:\/\/gym.openai.com\/<\/a><\/h1>\n<h2>Gym is a toolkit for developing and comparing &#8230;. It supports teaching agents everything from <a href=\"https:\/\/gym.openai.com\/envs\/Humanoid-v1\">walking<\/a> to playing games like <a href=\"https:\/\/gym.openai.com\/envs\/Pong-ram-v0\">Pong<\/a> or <a href=\"https:\/\/gym.openai.com\/envs\/VideoPinball-ram-v0\">Pinball<\/a>.<br \/>\n<\/h2>\n<p>&quot;<br \/>\n<a href=\"https:\/\/gym.openai.com\/\">https:\/\/gym.openai.com\/<\/a><\/p>\n<p>&#8212;-<\/p>\n<p>&quot;Project Malmo integrates (deep) reinforcement learning, cognitive science, and many ideas from artificial intelligence. &quot;<\/p>\n<p><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/project\/project-malmo\/\">https:\/\/www.microsoft.com\/en-us\/research\/project\/project-malmo\/<\/a><\/p>\n<p>&#8212;-<\/p>\n<p><strong>DeepMind:<\/strong><br \/>\n&quot;DeepMind&#8217;s scientific mission is to push the boundaries of AI, developing systems that can learn to solve any complex problem without needing to be taught how&quot;<br \/>\n<a href=\"https:\/\/deepmind.com\/blog\/open-sourcing-deepmind-lab\/\">https:\/\/deepmind.com\/blog\/open-sourcing-deepmind-lab\/<\/a><\/p>\n<p>&#8212;<\/p>\n<p>UCL Course on RL<\/p>\n<p><a href=\"http:\/\/www0.cs.ucl.ac.uk\/staff\/d.silver\/web\/Teaching.html\">http:\/\/www0.cs.ucl.ac.uk\/staff\/d.silver\/web\/Teaching.html<\/a><\/p>\n<p><strong>Basics of RL<\/strong><\/p>\n<p><strong>From: <\/strong><a href=\"https:\/\/www.kdnuggets.com\/2018\/03\/5-things-reinforcement-learning.html\">https:\/\/www.kdnuggets.com\/2018\/03\/5-things-reinforcement-learning.html<\/a><br \/>\n&quot;<\/p>\n<ol>\n<li><strong>What is reinforcement learning? How does it relate with other ML techniques?<\/strong><\/li>\n<\/ol>\n<p>Reinforcement Learning(RL) is a type of machine learning technique that enables an agent to learn in an interactive environment by trial and error using feedback from its own actions and experiences.<\/p>\n<ol start=\"3\">\n<li><strong>What are some most used Reinforcement Learning algorithms?<\/strong><\/li>\n<\/ol>\n<p>Q-learning and SARSA (State-Action-Reward-State-Action) are two commonly used model-free RL algorithms.<\/p>\n<p>&quot;<\/p>\n<p><strong>Uses of RL<\/strong><\/p>\n<p>&quot; building AI for playing computer games&quot;<\/p>\n<p>&quot; robotics and industrial automation &quot;<\/p>\n<p>&quot;applications of RL include text summarization engines, dialog agents (text, speech) which can learn from user interactions and improve with time, learning optimal treatment policies in healthcare and RL based agents for online stock trading.&quot;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>&quot; Gym: https:\/\/gym.openai.com\/ Gym is a toolkit for developing and comparing &#8230;. It supports teaching agents everything from walking to playing games like Pong or Pinball. &quot; https:\/\/gym.openai.com\/ &#8212;- &quot;Project Malmo integrates (deep) reinforcement learning, cognitive science, and many ideas from artificial intelligence. &quot; https:\/\/www.microsoft.com\/en-us\/research\/project\/project-malmo\/ &#8212;- DeepMind: &quot;DeepMind&#8217;s scientific mission is to push the boundaries &hellip; <\/p>\n<p><a class=\"more-link btn\" href=\"http:\/\/bangla.sitestree.com\/?p=14752\">Continue reading<\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[182],"tags":[],"class_list":["post-14752","post","type-post","status-publish","format-standard","hentry","category---blog","item-wrap"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack-related-posts":[{"id":24971,"url":"http:\/\/bangla.sitestree.com\/?p=24971","url_meta":{"origin":14752,"position":0},"title":"AI Implementation Platforms: Reinforcement Learning Platforms and Applications: #Root","author":"Author-Check- Article-or-Video","date":"April 14, 2021","format":false,"excerpt":"\" Gym: https:\/\/gym.openai.com\/ Gym is a toolkit for developing and comparing .... It supports teaching agents everything from walking to playing games like Pong or Pinball. \" https:\/\/gym.openai.com\/ ---- \"Project Malmo integrates (deep) reinforcement learning, cognitive science, and many ideas from artificial intelligence. \" https:\/\/www.microsoft.com\/en-us\/research\/project\/project-malmo\/ ---- DeepMind: \"DeepMind's scientific mission\u2026","rel":"","context":"In &quot;FromSitesTree.com&quot;","block_context":{"text":"FromSitesTree.com","link":"http:\/\/bangla.sitestree.com\/?cat=1917"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":19601,"url":"http:\/\/bangla.sitestree.com\/?p=19601","url_meta":{"origin":14752,"position":1},"title":"Reinforcement Learning Examples\/DQN Examples","author":"Sayed","date":"February 2, 2021","format":false,"excerpt":"What I was looking for is: A DQN (Deep Q Learning Neural Network) or a Reinforcement Learning example that can learn from existing simulation data, and then can use that learning to interactively optimize an objective. The challenge will be: Whether my data can be learned from (whether the format\/structure\u2026","rel":"","context":"In &quot;\u09ac\u09cd\u09b2\u0997 \u0964 Blog&quot;","block_context":{"text":"\u09ac\u09cd\u09b2\u0997 \u0964 Blog","link":"http:\/\/bangla.sitestree.com\/?cat=182"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":26368,"url":"http:\/\/bangla.sitestree.com\/?p=26368","url_meta":{"origin":14752,"position":2},"title":"Reinforcement Learning Examples\/DQN Examples #Root","author":"Author-Check- Article-or-Video","date":"April 22, 2021","format":false,"excerpt":"What I was looking for is: A DQN (Deep Q Learning Neural Network) or a Reinforcement Learning example that can learn from existing simulation data, and then can use that learning to interactively optimize an objective. The challenge will be: Whether my data can be learned from (whether the format\/structure\u2026","rel":"","context":"In &quot;FromSitesTree.com&quot;","block_context":{"text":"FromSitesTree.com","link":"http:\/\/bangla.sitestree.com\/?cat=1917"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":19382,"url":"http:\/\/bangla.sitestree.com\/?p=19382","url_meta":{"origin":14752,"position":3},"title":"Resources: Reinforcement Learning and Deep Reinforcement Learning","author":"Sayed","date":"January 28, 2021","format":false,"excerpt":"Platform: https:\/\/gym.openai.com\/ Code Examples: https:\/\/towardsdatascience.com\/using-deep-q-learning-in-fifa-18-to-perfect-the-art-of-free-kicks-f2e4e979ee66?gi=b96ce845729c https:\/\/becominghuman.ai\/reinforcement-learning-with-fifa-and-keras-85ec792e25b2 https:\/\/towardsdatascience.com\/reinforcement-learning-demystified-solving-mdps-with-dynamic-programming-b52c8093c919 https:\/\/github.com\/openai\/gym\/blob\/master\/gym\/envs\/toy_text\/nchain.py Theory https:\/\/towardsdatascience.com\/introduction-to-various-reinforcement-learning-algorithms-i-q-learning-sarsa-dqn-ddpg-72a5e0cb6287 https:\/\/cecas.clemson.edu\/ayalew\/Papers\/Vehicle%20Systems%20Dynamics%20and%20Control\/Papers\/A%20Saturation%20Balancing%20Control%20Method%20for%20Enhancing%20Dynamic%20Vehicle%20Stability\/IJVD%2061_1-4_Paper%203.pdf https:\/\/arxiv.org\/pdf\/1712.01815.pdf *** . *** *** . *** . *** . *** Courses: http:\/\/Training.SitesTree.com (Big Data, Cloud, Security, Machine Learning) Blog: http:\/\/Bangla.SaLearningSchool.com, http:\/\/SitesTree.com 8112223 Canada Inc.\/JustEtc: http:\/\/JustEtc.net Shop Online: https:\/\/www.ShopForSoul.com\/ Linkedin: https:\/\/ca.linkedin.com\/in\/sayedjustetc Medium: https:\/\/medium.com\/@SayedAhmedCanada","rel":"","context":"In &quot;\u09ac\u09cd\u09b2\u0997 \u0964 Blog&quot;","block_context":{"text":"\u09ac\u09cd\u09b2\u0997 \u0964 Blog","link":"http:\/\/bangla.sitestree.com\/?cat=182"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":14773,"url":"http:\/\/bangla.sitestree.com\/?p=14773","url_meta":{"origin":14752,"position":4},"title":"Reinforcement Learning Concepts Explained in a Simple Way.","author":"Sayed","date":"May 17, 2019","format":false,"excerpt":"Reinforcement Learning Concepts Explained in a Simple (or not) Way. This is intended for the beginners who want to know the concepts used in Reinforcement Learning i.e. Interactive Learning. Reinforcement Learning is also one aspect of Machine Learning, Data Science, and AI Summary of Tabular Methods in Reinforcement Learning Comparison\u2026","rel":"","context":"In &quot;AI ML DS RL DL NN NLP Data Mining Optimization&quot;","block_context":{"text":"AI ML DS RL DL NN NLP Data Mining Optimization","link":"http:\/\/bangla.sitestree.com\/?cat=1910"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":14751,"url":"http:\/\/bangla.sitestree.com\/?p=14751","url_meta":{"origin":14752,"position":5},"title":"Applications and Research on Reinforcement Learning","author":"Sayed","date":"May 3, 2019","format":false,"excerpt":"\"WHAT ARE MAJOR REINFORCEMENT LEARNING ACHIEVEMENTS & PAPERS FROM 2018?\" Reference: https:\/\/www.topbots.com\/most-important-ai-reinforcement-learning-research\/#ai-rl-paper-2018-10 \" Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures Temporal Difference Models: Model-Free Deep RL for Model-Based Control Addressing Function Approximation Error in Actor-Critic Methods\u2026","rel":"","context":"In &quot;\u09ac\u09cd\u09b2\u0997 \u0964 Blog&quot;","block_context":{"text":"\u09ac\u09cd\u09b2\u0997 \u0964 Blog","link":"http:\/\/bangla.sitestree.com\/?cat=182"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"_links":{"self":[{"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/posts\/14752","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=14752"}],"version-history":[{"count":0,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/posts\/14752\/revisions"}],"wp:attachment":[{"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=14752"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=14752"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=14752"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}