CS285

CS 285 at UC Berkeley

Deep Reinforcement Learning

Lectures: Mon/Wed 10-11:30 a.m., Soda Hall, Room 306


Lectures will be streamed and recorded. The course is not being offered as an online course, and the videos are provided only for your personal informational and entertainment purposes. They are not part of any course requirement or degree-bearing university program.


Piazza is the preferred platform to communicate with the instructors. However, if for some reason you wish to contact the course staff by email, use the following email address: cs285fall2019@googlegroups.com.

Looking for deep RL course materials from past years?

Recordings of lectures from fall 2018 are here, and materials from previous offerings are here.
  • Instructor Sergey Levine

    svlevine@eecs.berkeley.edu

    Office Hours: Wed 11.30-12.30pm, Soda 347 alcove

  • Head GSI Frederik Ebert

    febert@eecs.berkeley.edu

    Office Hours: Thurs 9-10am, Soda 347 alcove

  • GSI Avi Singh

    avisingh@berkeley.edu

    Office Hours: Mon 4-5pm, Soda 347 alcove

  • GSI Kelvin Xu

    kelvinxu@berkeley.edu

    Office Hours: Fri 10-11am, Soda 347 alcove

  • GSI Anusha Nagabandi

    nagaban2@berkeley.edu

    Office Hours: Mon 11.30-12.30pm, Soda 347 alcove

Week 1 Overview

Course Introduction, Imitation Learning

Week 2 Overview

Imitation Learning

Week 4 Overview

Policy Gradients and Actor Critic

Week 5 Overview

Value Functions and Q-learning

Week 6 Overview

Advanced Policy Gradients and Model-based learning

Week 7 Overview

Advanced Model Learning and Imitating Optimal Controllers

Week 9 Overview

Inverse Reinforcement Learning and multi-task learning

Week 10 Overview

Parallelism for RL

Week 11 Overview

Exploration

Week 12 Overview

Meta-learning

Week 13 Overview

Information Theory, Challenges, Open Problems