CS 185/285 at UC Berkeley
Deep Reinforcement Learning
Lectures: 9 - 10 am on Wednesdays and 8 - 10 am on Fridays, both in Hearst Annex A1
Announcement: Homework 1 (Imitation Learning) is out and due Feb 11th at 11:59 pm.
Announcement: Please complete the CS 185/285 enrollment form if you plan to take the course.
Lecture recordings from the current (Spring 2026) offering of the course: TBD (link coming soon).
Looking for deep RL course materials from past years?
Recordings of lectures from Fall 2023 are here, and materials from previous offerings are here.Email all staff (preferred): cs285-staff-sp2026@lists.eecs.berkeley.edu
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Instructor Sergey Levine
svlevine@eecs.berkeley.edu
Office Hours: Wednesdays 8 - 9 AM in Hearst Annex A1
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GSI Vivek Myers
vmyers@berkeley.edu
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Week 1 Overview
Course Intro & Imitation Learning
Week 2 Overview
Imitation Learning & RL Basics
Week 3 Overview
Policy Gradients & Actor Critic
Homeworks
See Syllabus for more information (including rough schedule).
- Homework 1: Imitation Learning
- Homework 2: TBD
- Homework 3: TBD
- Homework 4: TBD
- Homework 5: TBD
Lecture Slides
See Syllabus for more information.
- Lecture 1: Introduction
- Lecture 2: Behavioral Cloning
- Lecture 3: Behavioral Cloning Part 2
- Lecture 4: RL Basics
- Lecture 5: Policy Gradients
- Lecture 6: TBD
- Lecture 7: TBD
- Lecture 8: TBD
- Lecture 9: TBD
- Lecture 10: TBD
- Lecture 11: TBD
- Lecture 12: TBD
- Lecture 13: TBD
- Lecture 14: TBD
- Lecture 15: TBD
- Lecture 16: TBD
- Lecture 17: TBD
- Lecture 18: TBD
- Lecture 19: TBD
- Lecture 20: TBD
- Lecture 21: TBD
- Lecture 22: TBD
- Lecture 23: TBD
Discussion Section Slides
See Syllabus for more information.
- Section 1: PyTorch Tutorial
- Section 2 Part 1: Probability Review
- Section 2 Part 2: BC Distributional Shift
- Section 3: TBD
- Section 4: TBD
- Section 5: TBD
- Section 6: TBD
- Section 7: TBD
- Section 8: TBD
- Section 9: TBD
- Section 10: TBD
- Section 11: TBD
- Section 12: TBD