RL: Lecture Schedule
Note: See the "Coding Proficiency Self-Check" below for details about programming requirements.
Lecture times and location:
- Tuesdays and Fridays, 14.10–15.00
- Appleton Tower Lecture Theatre 1
Lecture slides are linked in the table below. Slides may be updated, and the new slides will be uploaded at least 24h before the lecture time.
The course follows the 2nd-edition RL book by Richard Sutton and Andrew Barto, which can be downloaded for free here. Required reading from the RL book for each lecture is given in the last slide of the lecture and in the table below.
| Week | Date | Topic (slides) | Required Reading |
| 1 | 16 January '24 | Introduction | Ch. 1 (1.1–1.4); Coding Proficiency Self-Check |
| 19 January '24 | Multi-armed bandits | Ch. 2 (2.1–2.8) | |
| 2 | 23 January '24 | Markov decision processes | Ch. 3 (3.1–3.7) |
| 26 January '24 | Dynamic programming | Ch. 4 (4.1–4.7) | |
| 3 | 30 January '24 | Monte Carlo methods | Ch. 5 (5.1–5.7) |
| 02 February '24 | Temporal-difference learning | Ch. 6 (6.1–6.2, 6.4–6.6), Ch. 7 (7.1–7.3) | |
| 4 | 06 February '24 | Planning and learning | Ch. 8 (8.1–8.3, 8.10–8.11) |
| 09 February '24 | Tutorial lecture: building a complete RL system | Demo code | |
| 5 | 13 February '24 | Coursework introduction | Coursework |
| 16 February '24 | Value function approximation | Ch. 9 (9.1–9.5), Ch. 10 (10.1), Ch. 11 (11.1) | |
| Flexible learning week (no lectures) | |||
| 6 | 27 February '24 | Policy gradient methods | Ch. 13 (13.1–13.5) |
| 01 March '24 | Deep reinforcement learning I | Topics not examined | |
| 7 | 05 March '24 | Deep reinforcement learning II | |
| 08 March '24 | Multi-agent reinforcement learning I | ||
| 8 | 12 March '24 (last lecture) | Multi-agent reinforcement learning II | |
License
All rights reserved The University of Edinburgh