📣 Workshop material for Week 2 is available here:
🔗 https://github.com/DeepRLCourse/Workshop-2-Material
🔗 https://github.com/DeepRLCourse/Workshop-2-Material
GitHub
GitHub - DeepRLCourse/Workshop-2-Material
Contribute to DeepRLCourse/Workshop-2-Material development by creating an account on GitHub.
📣 Important Announcement
You can submit your solutions for Homework 2 and Homework 3 together on March 2 (۱۲ اسفند).
You can submit your solutions for Homework 2 and Homework 3 together on March 2 (۱۲ اسفند).
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🚀 We will be live from 2:50 PM. Join us here:
https://www.youtube.com/@DeepRLCourse
🎙 Title: From Shortest Paths to Value Iteration to Q-Learning
👨🏫 Speaker: Chris Watkins (Professor of Computer Science, Royal Holloway)
https://www.youtube.com/@DeepRLCourse
🎙 Title: From Shortest Paths to Value Iteration to Q-Learning
👨🏫 Speaker: Chris Watkins (Professor of Computer Science, Royal Holloway)
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🚀 We will be live from 5:20 PM. Join us here:
https://www.youtube.com/@DeepRLCourse
🎙 Title: Assessing the Robustness of Deep RL Algorithms
👨🏫 Speaker: Michael L. Littman (Brown University, Humanity-Centered Robotics Initiative)
https://www.youtube.com/@DeepRLCourse
🎙 Title: Assessing the Robustness of Deep RL Algorithms
👨🏫 Speaker: Michael L. Littman (Brown University, Humanity-Centered Robotics Initiative)
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Lecture_4_Summary.pdf
389.3 KB
🎓 Summary of Lecture 4 📚
🔗 Quiz Link: https://forms.gle/AeiroVwcK7K5AKMNA
🕐 Deadline: 1:30 PM (before the class)
Stay on track and get it done! 🚀
🔗 Quiz Link: https://forms.gle/AeiroVwcK7K5AKMNA
🕐 Deadline: 1:30 PM (before the class)
Stay on track and get it done! 🚀
📣 Website Updated with Last Week’s Material!
Don't forget to take a look at the slides for today's lecture before the class:
🔗 https://deeprlcourse.github.io/lectures/week3/#lecture-5
Stay on track and keep learning! 🚀📚
Don't forget to take a look at the slides for today's lecture before the class:
🔗 https://deeprlcourse.github.io/lectures/week3/#lecture-5
Stay on track and keep learning! 🚀📚
deeprlcourse.github.io
Week 3: Policy-Based Methods - Deep RL Course
This page contains the lecture materials for Week 3 of the Deep Reinforcement Learning course, including video recordings, slides, and summaries.
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📣 Feedback Form for Summary & Quizzes of Lecture 1 to 4
🌐 https://forms.gle/n3FiZzQjyeSKTEo88
⏰ Deadline: Mar 2, 12 Midnight
🌐 https://forms.gle/n3FiZzQjyeSKTEo88
⏰ Deadline: Mar 2, 12 Midnight
📣 Screen record of Lecture 5 is Out!
🎥 https://www.youtube.com/watch?v=6V26_jje_ZE
🎥 https://www.youtube.com/watch?v=6V26_jje_ZE
YouTube
Lecture 5 | Policy-Based Methods | Spring 25 (Screen Record)
Welcome to the 5th lecture of our Spring 2025 Deep RL Course! 🚀
In this session, we dive into the policy-based methods 🤖
💡 Want more resources?
Get the slides and extra goodies here:
🔗 https://deeprlcourse.github.io/lectures/week3
Stay Connected:
✉️ …
In this session, we dive into the policy-based methods 🤖
💡 Want more resources?
Get the slides and extra goodies here:
🔗 https://deeprlcourse.github.io/lectures/week3
Stay Connected:
✉️ …
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📣 Course Notes for <Week 2: Value-based Methods> are Out!
🌐 https://deeprlcourse.github.io/course_notes/value-based
🌐 https://deeprlcourse.github.io/course_notes/value-based
deeprlcourse.github.io
Week 2: Value-based Methods - Deep RL Course
This page delves into the foundational concepts and methods of value-based reinforcement learning. It covers the Bellman equations, dynamic programming techniques like value iteration and policy iteration, Monte Carlo methods for prediction and control, and…
📣 Important Announcement
Today's lecture (۷ اسفند) will be held online at 1:30 PM. Please join us via the following link:
🌐 https://vc.sharif.edu/ch/rohban
Today's lecture (۷ اسفند) will be held online at 1:30 PM. Please join us via the following link:
🌐 https://vc.sharif.edu/ch/rohban
🫡4💯1
Lecture_5_Summary.pdf
2.2 MB
🎓 Summary of Lecture 5 📚
🔗 Quiz Link: https://forms.gle/x1c8USwQ3ujhgzJv5
🕐 Deadline: 1:30 PM (before the class)
Stay on track and get it done! 🚀
🔗 Quiz Link: https://forms.gle/x1c8USwQ3ujhgzJv5
🕐 Deadline: 1:30 PM (before the class)
Stay on track and get it done! 🚀
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🚀 Join Peter Stone’s Talk at Sharif University of Technology
🎙 Title: Multiagent RL: Cooperation and Competition
👨🏫 Speaker: Peter Stone (Professor of Computer Science, University of Texas at Austin)
📅 Date: Thursday (Feb 27, 2025)
🕗 Time: 3:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/M4QxTUWimGyvUmPv7
@DeepRLCourse
🎙 Title: Multiagent RL: Cooperation and Competition
👨🏫 Speaker: Peter Stone (Professor of Computer Science, University of Texas at Austin)
📅 Date: Thursday (Feb 27, 2025)
🕗 Time: 3:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/M4QxTUWimGyvUmPv7
@DeepRLCourse
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🚀 Professor Peter Stone recommends that all of you watch his talk at RLC 2024, noscriptd: "Practical Reinforcement Learning: Lessons from 30 Years of Research"
🎥 https://www.youtube.com/watch?v=5Dw4OoJK9Qw
🎥 https://www.youtube.com/watch?v=5Dw4OoJK9Qw
YouTube
Peter Stone - Practical Reinforcement Learning: Lessons from 30 Years of Research - RLC 2024
Edited by Gor Baghdasaryan
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PeterStoneTalk.pdf
201.1 KB
🚀 Professor Peter Stone also invites all of you to join his latest talk online on Zoom, noscriptd: "Outracing Champion Gran Turismo Drivers with Deep Reinforcement Learning"
📅 Date: Wednesday (Feb 26, 2025)
🕗 Time: 1:00 AM Iran Time
🔗 https://texastech.zoom.us/my/stas.tiomkin
🆔 Meeting ID: 554 589 4586
🔒 Passcode: 12345
📅 Date: Wednesday (Feb 26, 2025)
🕗 Time: 1:00 AM Iran Time
🔗 https://texastech.zoom.us/my/stas.tiomkin
🆔 Meeting ID: 554 589 4586
🔒 Passcode: 12345
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📣 SeyyedAli MirGhasemi, one of the designers of Homework 3, explains the homework for you:
🎥 https://www.youtube.com/watch?v=6Nbc6GYld7U
🎥 https://www.youtube.com/watch?v=6Nbc6GYld7U
YouTube
Homework 3 | Policy-Based Methods | Spring 25
Presented by SeyyedAli MirGhasemi
🔗 https://www.linkedin.com/in/sayyed-ali-mirghasemi-6033661b9
📂 Access the Homework:
🔗 https://deeprlcourse.github.io/homeworks/week3
Stay Connected:
✉️ deeprlcourse@gmail.com
🌐 https://deeprlcourse.github.io
📺 https:/…
🔗 https://www.linkedin.com/in/sayyed-ali-mirghasemi-6033661b9
📂 Access the Homework:
🔗 https://deeprlcourse.github.io/homeworks/week3
Stay Connected:
✉️ deeprlcourse@gmail.com
🌐 https://deeprlcourse.github.io
📺 https:/…
📣 Dariush Jamshidian has rerecorded Workshop 2 on Value-Based Methods for us, and it is now available here:
🔗 https://deeprlcourse.github.io/workshops/week2
🔗 https://deeprlcourse.github.io/workshops/week2
deeprlcourse.github.io
Week 2: Value-Based Methods - Deep RL Course
This page contains the workshop materials for Week 2 of the Deep Reinforcement Learning course. You can find links to the workshop recordings and notebooks.
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📣 Screen record of Lecture 6 is Out!
🎥 https://www.youtube.com/watch?v=LZSUB3XBwXI
🎥 https://www.youtube.com/watch?v=LZSUB3XBwXI
YouTube
Lecture 6 | Policy-Based Methods | Spring 25 (Screen Record)
Welcome to the 6th lecture of our Spring 2025 Deep RL Course! 🚀
In this session, we continue to dive into the policy-based methods 🤖
💡 Want more resources?
Get the slides and extra goodies here:
🔗 https://deeprlcourse.github.io/lectures/week3
Stay Connected:…
In this session, we continue to dive into the policy-based methods 🤖
💡 Want more resources?
Get the slides and extra goodies here:
🔗 https://deeprlcourse.github.io/lectures/week3
Stay Connected:…