{"id":76524,"date":"2024-12-27T17:02:24","date_gmt":"2024-12-27T17:02:24","guid":{"rendered":"http:\/\/bangla.sitestree.com\/?p=76524"},"modified":"2024-12-27T17:02:24","modified_gmt":"2024-12-27T17:02:24","slug":"reinforcement-learning-problem","status":"publish","type":"post","link":"http:\/\/bangla.sitestree.com\/?p=76524","title":{"rendered":"Reinforcement Learning Problem"},"content":{"rendered":"\n

Ref: https:\/\/www.cs.toronto.edu\/~jlucas\/teaching\/csc411\/lectures\/lec21_22_handout.pdf<\/a><\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Formulate: <\/strong><\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Read more from: https:\/\/www.cs.toronto.edu\/~jlucas\/teaching\/csc411\/lectures\/lec21_22_handout.pdf<\/a> <\/p>\n\n\n\n

What is a Policy (Deterministic Policy, Stochastic Policy)<\/p>\n\n\n\n

What is a Value Function<\/p>\n\n\n\n

What is a Model? What is Model Free. Markov Property for Model<\/p>\n\n\n\n

MDP Problems<\/p>\n\n\n\n

Exploration and Exploitation<\/p>\n\n\n\n

Bellman Equations<\/p>\n\n\n\n

<\/p>\n\n\n\n

Q-Learning<\/p>\n\n\n\n

Function Approximation for Large State Spaces<\/p>\n","protected":false},"excerpt":{"rendered":"

Ref: https:\/\/www.cs.toronto.edu\/~jlucas\/teaching\/csc411\/lectures\/lec21_22_handout.pdf Formulate: Read more from: https:\/\/www.cs.toronto.edu\/~jlucas\/teaching\/csc411\/lectures\/lec21_22_handout.pdf What is a Policy (Deterministic Policy, Stochastic Policy) What is a Value Function What is a Model? What is Model Free. Markov Property for Model MDP Problems Exploration and Exploitation Bellman Equations Q-Learning Function Approximation for Large State Spaces<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-76524","post","type-post","status-publish","format-standard","hentry","category-root","item-wrap"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack-related-posts":[{"id":14783,"url":"http:\/\/bangla.sitestree.com\/?p=14783","url_meta":{"origin":76524,"position":0},"title":"On Effective teaching and Learning and Course Design","author":"Sayed","date":"May 27, 2019","format":false,"excerpt":"Successful Lecturing: Presenting Information in Ways That Engage Effective Processing \" Lecturing has been criticized as ineffective relative to other methods of teaching that involve students as active participants in the learning process, not as passive observers. Lectures, though, are a fact of academic life. They are the most widely\u2026","rel":"","context":"In "\u09ac\u09cd\u09b2\u0997 \u0964 Blog"","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":14733,"url":"http:\/\/bangla.sitestree.com\/?p=14733","url_meta":{"origin":76524,"position":1},"title":"On Reinforcement Learning:","author":"Sayed","date":"April 17, 2019","format":false,"excerpt":"On Reinforcement Learning: Questions and Answers https:\/\/www.inf.ed.ac.uk\/teaching\/courses\/rl\/tutorials.html Monte Carlo: https:\/\/medium.com\/@zsalloum\/monte-carlo-in-reinforcement-learning-the-easy-way-564c53010511 TD in Reinforcement Learning, the Easy Way: Temporal Difference https:\/\/towardsdatascience.com\/td-in-reinforcement-learning-the-easy-way-f92ecfa9f3ce Implementations of TD Algorithms: https:\/\/github.com\/dennybritz\/reinforcement-learning\/tree\/master\/TD Learning and Planning: 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