📣 "Advanced Theory" Recitation
🕛 Tomorrow (Sunday June 1st) at 12:00 PM
🧑🏻🏫 Abdollah Zohrabi
🏬 Further Info on Class Location will be Provided in the Class Group
🧠 Don’t miss it—let's learn and explore together! 💡
🕛 Tomorrow (Sunday June 1st) at 12:00 PM
🧑🏻🏫 Abdollah Zohrabi
🏬 Further Info on Class Location will be Provided in the Class Group
🧠 Don’t miss it—let's learn and explore together! 💡
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🚀 Join Anne Collins’s Talk at Sharif University of Technology
🎙 Title: Insights from Cognitive Science into Fast and Flexible Learning
👨🏫 Speaker: Anne Collins (University of California, Berkeley; Department of Psychology; Helen Wills Neuroscience Institute)
📅 Date: Monday (June 2, 2025)
🕗 Time: 6:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/K74JT6zuCLzQSU15A
@DeepRLCourse
🎙 Title: Insights from Cognitive Science into Fast and Flexible Learning
👨🏫 Speaker: Anne Collins (University of California, Berkeley; Department of Psychology; Helen Wills Neuroscience Institute)
📅 Date: Monday (June 2, 2025)
🕗 Time: 6:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/K74JT6zuCLzQSU15A
@DeepRLCourse
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Lecture_27_Summary.pdf
427.5 KB
🎓 Summary of Lecture 27 📚
🔗 Quiz Link: https://forms.gle/sWQ9yqJ639MTbGFa7
🕐 Deadline: 1:30 PM (before the class)
Stay on track and get it done! 🚀
🔗 Quiz Link: https://forms.gle/sWQ9yqJ639MTbGFa7
🕐 Deadline: 1:30 PM (before the class)
Stay on track and get it done! 🚀
Lecture_28_Summary.pdf
1.2 MB
🎓 Summary of Lecture 28 📚
🔗 Quiz Link: https://forms.gle/Qm2LBkLXuqkxewp38
🕐 Deadline: 1:30 PM (before the class)
Stay on track and get it done! 🚀
🔗 Quiz Link: https://forms.gle/Qm2LBkLXuqkxewp38
🕐 Deadline: 1:30 PM (before the class)
Stay on track and get it done! 🚀
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🚀 Join Martha White’s Talk at Sharif University of Technology
🎙 Title: Better Actor-Critic Algorithms for RL
👨🏫 Speaker: Martha White (Associate Professor at the University of Alberta, Canada CIFAR AI Chair, and Fellow of the Alberta Machine Intelligence Institute)
📅 Date: Thursday (June 5, 2025)
🕗 Time: 7:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/eNRZSccp2eHEUdZz8
@DeepRLCourse
🎙 Title: Better Actor-Critic Algorithms for RL
👨🏫 Speaker: Martha White (Associate Professor at the University of Alberta, Canada CIFAR AI Chair, and Fellow of the Alberta Machine Intelligence Institute)
📅 Date: Thursday (June 5, 2025)
🕗 Time: 7:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/eNRZSccp2eHEUdZz8
@DeepRLCourse
❤7
📣 Poster Session Research Proposal, Grading, Timeline, & Details
🔗 https://deeprlcourse.github.io/poster_session
🔗 https://deeprlcourse.github.io/poster_session
deeprlcourse.github.io
Poster Session - Deep RL Course
This page provides all the details for the Poster Session, including guidelines for your research proposal, video presentation, poster design, and in-person session. It outlines submission deadlines, grading criteria, and bonus opportunities to help you showcase…
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🚀 Join Luis Serrano’s Talk at Sharif University of Technology
🎙 Title: The Role of Reinforcement Learning in Training and Fine-Tuning Large Language Models
👨🏫 Speaker: Luis Serrano (Founder and CEO of Serrano.Academy)
📅 Date: Thursday (June 5, 2025)
🕗 Time: 5:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/Pswm8oLMBfGyN16E8
@DeepRLCourse
🎙 Title: The Role of Reinforcement Learning in Training and Fine-Tuning Large Language Models
👨🏫 Speaker: Luis Serrano (Founder and CEO of Serrano.Academy)
📅 Date: Thursday (June 5, 2025)
🕗 Time: 5:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/Pswm8oLMBfGyN16E8
@DeepRLCourse
❤6🔥4
🚀 Join Marlos C. Machado’s Talk at Sharif University of Technology
🎙 Title: Representation-Driven Option Discovery in RL
👨🏫 Speaker: Marlos C. Machado (Assistant Professor at the University of Alberta, Alberta Machine Intelligence Institute Fellow, Canada CIFAR AI Chair through Amii, and a principal investigator in the Reinforcement Learning and Artificial Intelligence Group)
📅 Date: Friday (June 6, 2025)
🕗 Time: 6:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/11E9YdyMYWEPw4hLA
@DeepRLCourse
🎙 Title: Representation-Driven Option Discovery in RL
👨🏫 Speaker: Marlos C. Machado (Assistant Professor at the University of Alberta, Alberta Machine Intelligence Institute Fellow, Canada CIFAR AI Chair through Amii, and a principal investigator in the Reinforcement Learning and Artificial Intelligence Group)
📅 Date: Friday (June 6, 2025)
🕗 Time: 6:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/11E9YdyMYWEPw4hLA
@DeepRLCourse
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🚀 Join Christopher Amato’s Talk at Sharif University of Technology
🎙 Title: A Short Introduction to Cooperative Multi-Agent Reinforcement Learning
👨🏫 Speaker: Christopher Amato (Associate Professor in the Khoury College of Computer Sciences at Northeastern University)
📅 Date: Friday (June 6, 2025)
🕗 Time: 4:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/69VpNRoULDrjTPKz7
@DeepRLCourse
🎙 Title: A Short Introduction to Cooperative Multi-Agent Reinforcement Learning
👨🏫 Speaker: Christopher Amato (Associate Professor in the Khoury College of Computer Sciences at Northeastern University)
📅 Date: Friday (June 6, 2025)
🕗 Time: 4:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/69VpNRoULDrjTPKz7
@DeepRLCourse
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📣 Homework 11 is out!
⏰ Deadline: July 4th (۱۳ تیر) 11:59 PM
🌐 https://deeprlcourse.github.io/homeworks/week11
⏰ Deadline: July 4th (۱۳ تیر) 11:59 PM
🌐 https://deeprlcourse.github.io/homeworks/week11
deeprlcourse.github.io
HW11: Imitation & Inverse RL - Deep RL Course
This page contains the homework assignment for Week 11 of the Deep Reinforcement Learning course, focusing on Imitation & Inverse RL.
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📣 Homework 12 is out!
⏰ Deadline: July 4th (۱۳ تیر) 11:59 PM
🌐 https://deeprlcourse.github.io/homeworks/week12
⏰ Deadline: July 4th (۱۳ تیر) 11:59 PM
🌐 https://deeprlcourse.github.io/homeworks/week12
deeprlcourse.github.io
HW12: Offline Methods - Deep RL Course
This page contains the homework assignment for Week 12 of the Deep Reinforcement Learning course, focusing on Offline Methods.
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📣 Richard Sutton's Talk at Reinforcement Learning Conference 2025:
https://youtube.com/watch?v=gEbbGyNkR2U
https://youtube.com/watch?v=gEbbGyNkR2U
YouTube
Rich Sutton, The OaK Architecture: A Vision of SuperIntelligence from Experience - RLC 2025
As AI has become a huge industry, to a large extent it has lost its way. What is needed to get us back on track to true intelligence? We need agents that learn continually. We need world models and planning. We need knowledge that is high-level and learnable.…
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📣 Michael Littman's Talk at Reinforcement Learning Conference 2025:
https://www.youtube.com/watch?v=orxCYhb9iDI
https://www.youtube.com/watch?v=orxCYhb9iDI
YouTube
Michael Littman, Efficient RL/AI via Interaction and Teaching - RLC 2025
Splashy RL/AI headlines sometimes obscure a deep truth---we can't really tell if these systems reliably do what we train them to do. In this talk, I assert that theory, that is, mathematical analysis, is a critical conceptual and even practical tool for helping…
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📣 Peter Dayan's Talk at Reinforcement Learning Conference 2025:
https://www.youtube.com/watch?v=2OOGxkqM2oI
https://www.youtube.com/watch?v=2OOGxkqM2oI
YouTube
Peter Dayan, The Marriage of Natural & Engineered Reinforcement Learning - RLC 2025
Natural and engineered reinforcement learning (RL) have been on- and off-again bedfellows for more than 70 years. There are many themes that are actually central to both, but they are often couched and characterized in different terms. This is true of debates…
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📣 Stanford Spring 2025 Deep Reinforcement Learning Course:
👩🏻🏫 Prof. Chelsea Finn
🔗 https://cs224r.stanford.edu
🎥 https://www.youtube.com/watch?v=EvHRQhMX7_w&list=PLoROMvodv4rPwxE0ONYRa_itZFdaKCylL
👩🏻🏫 Prof. Chelsea Finn
🔗 https://cs224r.stanford.edu
🎥 https://www.youtube.com/watch?v=EvHRQhMX7_w&list=PLoROMvodv4rPwxE0ONYRa_itZFdaKCylL
YouTube
Stanford CS224R Deep Reinforcement Learning | Spring 2025 | Lecture 1: Class Intro
View course details: https://online.stanford.edu/courses/xcs224r-deep-reinforcement-learning
April 2, 2025
This lecture covers:
• Class introduction
• Markov Decisions Processes
• Why study deep reinforcement learning?
• Intro to modeling behavior and reinforcement…
April 2, 2025
This lecture covers:
• Class introduction
• Markov Decisions Processes
• Why study deep reinforcement learning?
• Intro to modeling behavior and reinforcement…
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