Timetable
Fall 2018
| 2018-09-06 | Lecture 1: Introduction and Course Overview (slides) (test) | (watch in the class together) |
| 2018-09-13 | Lecture 2: Supervised Learning and Imitation (slides) (test) | (watch home, test and discussion in class) |
| 2018-09-20 | Lecture 3: TensorFlow and Neural Nets Review Session (slides) (notebook) | (watch home if needed, no test) |
| Homework 1: Imitation Learning (code) | (solution presentations, deadline next day) | |
| 2018-09-27 | Lecture 4: Reinforcement Learning Introduction (slides) (test) | (watch home, test and discussion in class) |
| 2018-10-04 | Lecture 5: Policy Gradients Introduction (slides) (test) | (watch home, test and discussion in class) |
| 2018-10-11 | Homework 2: Policy Gradients (code) | (solution presentations 1-5, deadline next day) |
| 2018-10-18 | Lecture 6: Actor-Critic Introduction (slides) (test) | (watch home, test and discussion in class) |
| 2018-10-25 | Homework 2: Policy Gradients (code) | (solution presentations 6-8, deadline next day) |
| 2018-11-01 | Lecture 7: Value Functions and Q-Learning (slides) (test) | (watch home, test and discussion in class) |
| 2018-11-08 | Lecture 8: Advanced Q-Learning Algorithms (slides) (test) | (watch home, test and discussion in class) |
| 2018-11-15 | Homework 3: Q-Learning and Actor-Critic (code) | (solution presentations, deadline next day) |
| 2018-11-22 | Lecture 9: Advanced Policy Gradients (slides) (test) | (watch home, test and discussion in class) |
| 2018-11-29 | Lecture 10: Optimal Control and Planning (slides) (test) | (watch home, test and discussion in class) |
| 2018-12-06 | Lecture 11: Model-Based Reinforcement Learning (slides) (test) | (watch home, test and discussion in class) |
| 2018-12-13 | Homework 4: Model-Based RL (code) | (solution presentations, deadline next day) |
| 2018-12-20 | Lecture 12: Advanced Model-Based Reinforcement Learning (slides) | (watch home, test and discussion in class) |
| ??? | Lecture 13: Model-Based RL and Policy Learning (slides) | (watch home, test and discussion in class) |
Spring 2019
| 2019-02-12 | Lecture 14: Variational Inference and Generative Models (slides) (test) | (watch home, test and discussion in class) |
| 2019-02-19 | Lecture 15: Reframing Control as an Inference Problem (slides) (test) | (watch home, test and discussion in class) |
| 2019-02-26 | Lecture 16: Inverse Reinforcement Learning (slides) (test) | (watch home, test and discussion in class) |
| 2019-03-05 | Project milestone 1 | (what task/environment, what is observation space, what is action space, what is reward) |
| Homework 5b: Advanced Topics - Soft Actor-Critic (code) | (solution presentations, deadline next day) | |
| 2019-03-12 | Lecture 17: Exploration: Part 1 (slides) (test) | (watch home, test and discussion in class) |
| 2019-03-19 | Lecture 18: Exploration: Part 2 (slides) | (watch home, test and discussion in class) |
| 2019-03-26 | Project milestone 2 | (what algorithm? what codebase? what infrastructure for training?) |
| Homework 5a: Advanced Topics - Exploration (code) | (solution presentations, deadline next day) | |
| 2019-04-02 | Lecture 19: Transfer and Multi-Task Learning (slides) (test) | (watch home, test and discussion in class) |
| 2019-04-09 | Lecture 20: Meta Reinforcement Learning by Chelsea Finn (slides) (test) | (watch home, test and discussion in class) |
| 2019-04-16 | Lecture 21: Distributed RL by Richard Liaw & Eric Liang (slides) (slides2) (test) | (watch home, test and discussion in class) |
| 2019-04-23 | Project milestone 3 | (initial results, what improvements over initial results you plan?) |
| Homework 5c: Advanced Topics - Meta-Learning (code) | (solution presentations, deadline next day) | |
| 2019-04-30 | Lecture 22: Challenges in Deep Reinforcement Learning (test) | (watch home, test and discussion in class) |
| 2019-05-07 | Guest Lecture: Reinforcement learning for Recommender Systems: Some Foundational and Practical Issues by Craig Boutilier | (watch home or in class, no test) |
| 2019-05-14 | Guest Lecture: Real-World Robot Learning:Safety and Flexibility by Gregory Kahn (slides) | (watch home or in class, no test) |
| 2019-05-21 | Guest Lecture: AutoML: Automated Machine Learning by Barret Zoph & Quoc Le (slides) | (watch home or in class, no test) |
| 2019-05-28 | Project presentations | |